九州大学 研究者情報
発表一覧
髙木 英行(たかぎ ひでゆき) データ更新日:2021.05.21

教授 /  芸術工学研究院 デザイン人間科学部門 モデリング・最適化


学会発表等
1. 熊燕然,髙木英行, 進化計算による知識獲得, 第19回進化計算学会研究会, 2021.03.
2. 鐘睿,髙木英行, 大規模最適化問題へのスパースモデリング導入, 第19回進化計算学会研究会, 2021.03.
3. Matthias Harvey,髙木英行, 進化計算の初期化手法の比較, 第19回進化計算学会研究会, 2021.03.
4. YU, Jun, TAKAGI, Hideyuki, Accelerating Fireworks Algorithm with Dynamic Population Size Strategy, Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS&ISIS2020), 2020.12, A dynamic population size strategy is proposed for the fireworks algorithm (FWA) to adjust the population size based to the search results of the current generation. When the currently found optimal individual is updated, a linear decreasing method is activated to maintain an efficient exploitation speed. The population size is reduced by 1 until the minimum pre-set population size is reached, then the population size remains unchanged. Otherwise, we randomly generate a larger population size than the initial population and expand the explosion amplitudes of all firework individuals artificially, which the expectation that we can escape current local minima. To analyze the effectiveness of the proposed strategy, we combined it with the enhanced FWA (EFWA) together, and run the EFWA and (the EFWA + our proposed strategy) on 28 CEC 2013 benchmark functions in three different dimensions. Each function is run 30 trial times independently, and the Wilcoxon signed-rank test is applied to check significant differences. The statistical results showed that the proposed dynamic population size strategy can not only achieve a faster convergence speed for the FWA but also can jump out of trapped local minima more easily to maintain a higher performance, especially for high-dimensional problems..
5. INOUE, Makoto, MATSUMOTO, Hibiki, TAKAGI, Hideyuki, Acceptability of a Decision Maker to Handle Multi-objective Optimization on Design Space, Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS&ISIS2020), 2020.12, We introduce the acceptability of a decision maker to handle evolutionary multi-objective optimization (EMO) on design space, while most of EMO research tries to find many solutions on an objective space and passes them to a decision maker. Unlike this conventional EMO approaches, our approach decides maker's model with the concept of acceptability and introduces it in EMO search. Especially, this approach works well when qualitative factors, such as the decision maker's experience and knowledge on a task, are a part of evaluations. Acceptability functions for each of objectives are aggregated firstly, and the aggregated acceptability forms contours on an objective space and is mapped on a design space. The acceptability contours on a design space can narrow down the area of solutions. We could find better solutions in our experiments than the conventional approach of searching solutions on an objective space..
6. 余俊,髙木英行, 改良型偵察戦略:花火アルゴリズムへの応用, 第18回進化計算学会研究会, 2020.09.
7. 余俊,髙木英行, 多種生成戦略を導入した植物進化アルゴリズム, 第17回進化計算学会研究会, 2020.02.
8. 余俊,高木英行, 花火個体数の適応型花火アルゴリズム, 進化計算シンポジウム 2019, 2018.12.
9. 李宇豪, 余俊,高木英行, Nearest-better Clustering法の補完ニッチ手法, 進化計算シンポジウム 2019, 2018.12.
10. LI, Yuhao, YU, Jun, TAKAGI, Hideyuki, Niche Method Complementing the Nearest-better Clustering, 2019 IEEE Symposium Series on Computational Intelligence (SSCI2019), 2019.12, We propose a two-stage niching algorithm that separates local optima areas in the first stage and finds the optimum point of each area using any optimization technique in the second stage. The proposed first stage has complementary characteristics to the shortcoming of Nearest-better Clustering (NBC). We introduce a weighted gradient and distance-based clustering method (WGraD) and two methods for determining its weights to find out niches and overcome NBC. The WGraD creates spanning trees by connecting each search point to other suitable one decided by weighted gradient information and weighted distance information among search points. Since weights influence its clustering result, we propose two weight determination methods 1 and 2. The weight determination method 1 We combine these methods into WGrad, i.e. WGraD1 and WGraD2, and compare the characteristics of NBC, WGraD1, and WGraD2 using differential evolution (DE) as a baseline search algorithm for obtaining the optimum of each niche after clustering local areas. We design a controlled experiment and run (NBC + DE), (WGraD1 + DE) and (WGraD2 + DE) on 8 benchmark functions from CEC 2015 test suite for single objective multiniche optimization. The experimental results confirmed that the proposed strategy can overcome the shortcoming of NBC and be a complementary niche method of NBC.
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11. YU, Jun, TAKAGI, Hideyuki, Accelerating Vegetation Evolution with Mutation Strategy and Gbased Growth Strategy, 2019 IEEE Symposium Series on Computational Intelligence (SSCI2019), 2019.12, We propose two strategies, mutation strategy and Gbased growth strategy, to enhance the performance of standard vegetation evolution (VEGE) that simulates the growth and reproduction of vegetation repeatedly to find the global optimum. We introduce two different mutation methods into the growth period and the maturity period individually to increase the diversity of population by simulating different types of mutations in real plants. Inspired by various growth patterns of real plants, the Gbased growth strategy is proposed to replace a completely random growth operation of original VEGE and bias all non-optimal individuals to grow towards the current best area. We design a series of controlled experiments to evaluate the performance of our proposed strategies using 28 benchmark functions from CEC2013 suite with three different dimensions. The experimental results confirmed the mutation strategy can increase the diversity and the Gbased growth strategy plays an important role in accelerating convergence. Besides, the combination of both strategies can further improve the VEGE performance. .
12. YU, Jun and TAKAGI, Hideyuki, Performance Analysis of Vegetation Evolution, 2019 IEEE International Conference on Systems, Man, and Cybernetics (SMC2019), 2019.10, We focus on analyzing the impact of operations of a proposed Vegetation evolution (VEGE) algorithm on its performance rather than compare it with other EC algorithms, i.e., investigate the impact of each component of the VEGE algorithm on its performance. To further analyze the performance of VEGE algorithm, we design a series of controlled experiments to investigate the contribution of each VEGE component by running them on 28 benchmark functions of 3 different dimensions. Subsequently, we summarize some our experiences on setting VEGE parameters to apply the VEGE to optimization tasks. The experimental results reveal that the maturity operation has a critical impact on performance and the number of growth operations of an individual is set as small as possible, while the number of generated seed individuals is not an important factor. Besides, we discover that population size should be gradually increased as the dimension increases. Finally, we point out several potential research directions..
13. Yuhao Li, Jun Yu, Hideyuki Takagi, Ying Tan, Accelerating Fireworks Algorithm with Weight-based Guiding Sparks, 10th International Conference on Swarm Intelligence (ICSI2019), 2019.07, [URL].
14. Jun Yu, Hideyuki Takagi, Ying Tan, Fireworks Algorithm for Multimodal Optimization Using a Distance-based Exclusive Strategy, 2019 IEEE Congress on Evolutionary Computation (CEC2019), 2019.06, [URL], We propose a distance-based exclusive strategy to extend fireworks algorithm as a niche method to find out multiple global/local optima. This strategy forms sub-groups consisting of a firework individual and its generated spark individuals, each sub-group is guaranteed not to search overlapped areas each other. Finally, firework individuals are expected to find different global/local optima. The proposed strategy checks the distances between a firework and other fireworks which fitness is better than that of the firework. If the distance between two firework individuals is shorter than the sum of their searching radius, i.e. amplitude of firework explosions, these two firework individuals are considered to search overlapped area. Thus, the poor firework is removed and replaced by its opposite point to track multiple optima. To evaluate the performance of our proposed strategy, enhanced fireworks algorithm (EFWA) is used as a baseline algorithm and combined with our proposal. We design a controlled experiment, and run EFWA and (EFWA + our proposal) on 8 benchmark functions from CEC 2015 test suite, that is dedicated to single objective multi-niche optimization. The experimental results confirmed that the proposed strategy can find multiple different optima in one trial run..
15. 余俊,髙木英行, 距離ベース排他戦略導入によるニッチ花火アルゴリズム, 第15回進化計算学会研究会, 2019.03, [URL].
16. 余俊,高木英行, 植物進化アルゴリズムの性能解析, 進化計算シンポジウム 2018, 2018.12.
17. Jun Yu, Hideyuki Takagi, Vegetation Evolution for Numerical Optimization, JPNSEC International Workshop on Evolutionary Computation, 2018.09, We propose a new population-based evolutionary algorithm (EA) by simulating vegetation growth and reproduction repeatedly to find a global optimal solution. In nature, many plants use various survival mechanism to guarantee thrive and their seeds disperse everywhere, then generated seeds root in a new suitable environment then repeat growth experience of their father. Inspired by this process, we develop a new optimization framework, where an individual consists of two periods: growth and maturity. In the growth period, each individual focus on exploitation through competing survival resources to achieve its better growth, while all individuals move to exploration by intraspecific cooperation to achieve the population continued. Therefore, the new proposal alternately performs two periods to balance exploitation and exploration. To evaluate the performance of our proposed algorithm, we compare it with the other three widely known algorithms in EA community, differential evolution (DE), particle swarm optimization (PSO) and enhanced fireworks algorithm (EFWA), and apply them to 28 benchmark functions from CEC2013 test suites of 2-dimensions (2-D), 10-D and 30-D with 30 trial runs each. The experimental results confirm that our proposal is effective and potential. Finally, we analyze the effects of the composition of our proposal on performance, and some open topics are given..
18. 本村駿乃介,高木英行, 受容度を用いた賃貸物件データベース検索に関する研究, 第34回ファジィシステムシンポジウム, 2018.09.
19. Hideyuki Takagi, Keisuke Ikeda and Weiqiang Lai, Human Awareness Support by Changing Values of Hidden Factors of Input Stimuli Dynamically, 9th IEEE International Conference on Awareness Science and Technology (iCAST 2018), 2018.09, We propose an awareness support system that helps a user to be aware of the reason of his/her evaluations. Based on our proposed definition of human awareness mechanism, we extract hidden factors of input information using an auto-encoder neural networks and implement its decoder part into an awareness support system. The big feature of this system is to let a user change the values of the extracted hidden factors manually and observe the system outputs that change according to the changes of hidden factors. Experimental results using a task of generating facial emotions with 21 human subjects have shown the effectiveness of this approach..
20. 余俊, 譚営,髙木英行, Scouting Strategy for Biasing Fireworks Algorithm Search to Promising Directions, Genetic and Evolutionary Computation Conference (GECCO2018), 2018.07, We propose a scouting strategy to find better searching directions in fireworks algorithm (FWA) to enhance its exploitation capability. It generates spark individuals from a firework individual one by one by checking if the generated spark climbs up to a better direction, and this process continues until spark individual climbing down is generated, while canonical FWA generates spark individuals around a firework individual at once. We can know potential search directions from the number of consciously climbing up sparks. Besides this strategy, we use a filtering strategy for a random selection of FWA, where worse sparks are eliminated when their fitness is worse than their parents, i.e. fireworks, and become unable to survive in the next generation. We combined these strategies with the enhanced FWA (EFWA) and evaluated using 28 CEC2013 benchmark functions. Experimental results confirm that the proposed strategies are effective and show better performance in terms of convergence speed and accuracy. Finally, we analyze their applicability and provide some open topics..
21. 余俊, 譚営,髙木英行, Accelerating Fireworks Algorithm with an Estimated Convergence Point, 9th Int. Conf. on Swarm Intelligence (ICSI’2018), 2018.06, We propose an acceleration method for the fireworks algorithms which uses a convergence point for the population estimated from moving vectors between parent individuals and their sparks. To improve the accuracy of the estimated convergence point, we propose a new type of firework, the {\em synthetic firework}, to obtain the correct of the local/global optimum in its local area’s fitness landscape. The synthetic firework is calculated by the weighting moving vectors between a firework and each of its sparks and replacing the worst firework individual in the next generation. We design a controlled experiment for evaluating the proposed strategy and apply it to 20 CEC2013 benchmark functions of 2-dimensions (2-D), 10-D and 30-D with 30 trial runs each. The experimental results and the Wilcoxon signed-rank test confirm that the proposed method can significantly improve the performance of the canonical firework algorithm..
22. 余俊, 譚営,髙木英行, 花火アルゴリズムへの偵察戦略導入, 第14回進化計算学会研究会, 2018.03.
23. 余俊, 髙木英行, 強制約条件付き最適化問題の2段階探索, 進化計算シンポジウム 2017, 2017.12.
24. 裴岩,高木英行, 推定収束点を用いた多目的最適化の高速化, 進化計算シンポジウム 2017, 2017.12.
25. 余俊, 髙木英行, Estimation of Convergence Points of Population Using an Individual Pool,, 10th International Workshop on Computational Intelligence & Applications(IWCIA2017), Hiroshima, Japan,, 2017.11.
26. 余俊, 髙木英行, 推定収束点を用いた対話型進化計算高速化の可能性, 第33回ファジィシステムシンポジウム, 2017.09.
27. 余俊, 髙木英行, 信頼性重みを導入した個体群の収束点推定精度の向上, 第13回進化計算学会研究会, 2017.09.
28. 髙木英行, 賃貸住宅多数目的探索のための受容度, 2017年度日本建築学会大会, 2017.08.
29. 井上誠, 裴岩, 髙木英行, 多数目的最適化を目指した設計受容度 -- 静粛超音速研究機をタスクとして--, 第12 回進化計算学会研究会プログラム, 2017.03.
30. 余俊, 髙木英行, 個体間距離順位とフィットネス順位に基づく局所解領域の推定, 第12 回進化計算学会研究会プログラム, 2017.03.
31. 余俊, 髙木英行, 局所個体群のfitnessに基づくfitness景観の勾配推定を導入した花火アルゴリズム, 進化計算シンポジウム2016, 2016.12.
32. 井上誠, 高橋瑞稀, 裴岩, 髙木英行, 受容度に基づく多数目的探索のお部屋探し, 第11回進化計算研究会, 2016.09.
33. 大西圭, 栗栖万理子, 佐藤太河, 髙木英行, 協調型インタラクティブ進化計算実行チームの形成支援システム, 第32回ファジィシステムシンポジウム, 2016.08, We investigate the combinatorial effect of evolutionary multi-objective optimization (EMO) with interactive evolutionary computation (IEC). The purposes and combination ways of several presented EMO+IEC researches are different. We evaluated seven combination ways of four EMO objectives given by fitness functions and one IEC objective given by a pseudo-IEC user outputting stable evaluation regardless repeated experiments in our previous experiments. In this paper, we extend experimental conditions to 39 and evaluate them: 3 pseudo-users * 13 combination ways of 4+1 objectives. We also consider features of this system..
34. 池田啓介, 髙木英行, ニューラルネットワークを用いた気づき支援システムに関する研究, 第32回ファジィシステムシンポジウム, 2016.08, We investigate the combinatorial effect of evolutionary multi-objective optimization (EMO) with interactive evolutionary computation (IEC). The purposes and combination ways of several presented EMO+IEC researches are different. We evaluated seven combination ways of four EMO objectives given by fitness functions and one IEC objective given by a pseudo-IEC user outputting stable evaluation regardless repeated experiments in our previous experiments. In this paper, we extend experimental conditions to 39 and evaluate them: 3 pseudo-users * 13 combination ways of 4+1 objectives. We also consider features of this system..
35. Yu Jun, Yan Pei, Hideyuki Takagi, Accelerating Evolutionary Computation Using Estimated Convergence Point, IEEE Congress on Evolutionary Computation (CEC2016), 2016.07.
36. 余俊, Hideyuki Takagi, 八重芯型花火アルゴリズム, 第10回進化計算研究会, 2016.03.
37. 裴岩, 余俊, Hideyuki Takagi, 推定収束点を用いた進化計算高速化の評価, 進化計算シンポジウム 2015, 2015.12.
38. 井上誠, Hideyuki Takagi, 進化的フロアプラン生成における選択確率の検討, 計測自動制御学会システム・情報部門学術講演会2015 (SSI2015), 2015.11.
39. Jun Yu, Hideyuki Takagi, Clustering of Moving Vectors for Evolutionary Computation, 7th Int. Conf. on Soft Computing and Pattern Recognition (SoCPaR2015), 2015.11.
40. Hideyuki Takagi, 井上誠, 裴岩, 多目的最適化への受容度概念の導入, 第9回進化計算研究会, 2015.09.
41. 余俊, Hideyuki Takagi, 多峰性最適化問題での局所最適解推定高度化のための補正法 -- 局所最適解が2個の場合 --, 第9回進化計算研究会, 2015.09.
42. Yan Pei, Hideyuki Takagi, Local Information of Fitness Landscape Obtained by Paired Comparison-Based Memetic Search for Interactive Differential Evolution, IEEE Congress on Evolutionary Computation (CEC2015), 2015.05.
43. Noboru Murata, Ryuei Nishii, Hideyuki Takagi, Yan Pei, Analytical Estimation of the Convergence Point of Populations, IEEE Congress on Evolutionary Computation (CEC2015), 2015.05, [URL].
44. 村田昇, Ryuei Nishii, 髙木 英行, 裴岩, 世代間移動ベクトル群の収束点推定法, 2014進化計算シンポジウム, 2014.12.
45. Makoto Inoue, Megumu Hiramoto, Muneyuki Unehara, Koichi Yamada, Takagi Hideyuki, Evaluation of Hybrid Optimization With EMO and IEC for Architectural Floor Planning, Joint 7th Int. Conf. on Soft Computing and Intelligent Systems and 15th Int. Symposium on Advanced Intelligent Systems (SCIS-ISIS2014), 2014.12, We investigate the combinatorial effect of evolutionary multi-objective optimization (EMO) with interactive evolutionary computation (IEC). The purposes and combination ways of several presented EMO and IEC researches are different. We evaluated seven combination ways of four EMO objectives given by fitness functions and one IEC objective given by a pseudo-IEC user outputting stable evaluation regardless repeated experiments in our previous experiments. In this paper, we extend experimental conditions to 39 and evaluate them: 3 pseudo-users × 13 combination ways of 4 + 1 objectives. We also consider features of this system. .
46. Takagi Hideyuki, Three Research Directions of Interactive Evolutionary Computation, 18th Online World Conference on Soft-Computing in Industrial Applications (WSC18), 2014.12, [URL], We overview three research directions of interactive evolutionary computation (IEC). The first direction is to extend IEC applications that are hard or impossible for other optimization approaches. The second one is to reduce unavoidable IEC user fatigue by improving IEC user interface, developing new evolutionary computation (EC) algorithms and EC operations that converge faster and are effective under the restricted IEC conditions, introducing an IEC user evaluation model, letting an IEC user intervene EC search, and others. The third one is a new research and is to use IEC as a tool for analyzing human characteristics indirectly by analyzing characteristics of the target system optimized based on an IEC user's psychological evaluation scale, which is somehow similar to reverse engineering..
47. Yan Pei, Hideyuki Takagi, Qiangfu Zhao, Yong Liu, A comprehensive analysis on optimization performance of chaotic evolution and its parameter distribution, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC 2014), 2014.10, In this paper, we analyse and discuss the relationship between optimization performance of chaotic evolution (CE) algorithm and distribution characteristic of chaotic parameter. CE is an evolutionary computation algorithm that simulates chaotic motion of a chaotic system in a search space for implementing optimization. However, its optimization performance, internal process mechanism and optimization principle are not well studied. In this paper, we investigate distribution characteristics of chaotic systems, which support chaotic parameter in CE algorithm. Compared with other two parameter generators, i.e., a quadratic-like random generator and an uniform random generator, CE algorithm with chaotic parameter generated by the logistic map ($\mu = 4$) shows better optimization performance significantly. We also make an algorithm comparison with differential evolution and an algorithm ranking by Friedman test and Bonferroni-Dunn test. The related topics on relationship between optimization performance of CE algorithm and chaotic parameter distribution are analysed and discussed. From these analyses and discussions, it indicates that chaotic parameter distribution is a significant factor that influences optimization performance of CE algorithm..
48. 井上誠, 平元萌, 畦原宗之, 山田耕一, 髙木英行, 擬似人間を用いた対話型進化的計算と進化的多目的最適化の組合せ検討 — 建築間取りをタスクとした評価実験 — , 第30回ファジィシステムシンポジウム, 2014.09, We investigate the combinatorial effect of evolutionary multi-objective optimization (EMO) with interactive evolutionary computation (IEC). The purposes and combination ways of several presented EMO+IEC researches are different. We evaluated seven combination ways of four EMO objectives given by fitness functions and one IEC objective given by a pseudo-IEC user outputting stable evaluation regardless repeated experiments in our previous experiments. In this paper, we extend experimental conditions to 39 and evaluate them: 3 pseudo-users * 13 combination ways of 4+1 objectives. We also consider features of this system..
49. 裴岩, 髙木 英行, Local Information of Fitness Landscape Obtained by Paired Comparison-based Memetic Search for Interactive Differential Evolution, 第7回 進化計算学会進化計算研究会, 2014.08.
50. 船木亮平, 髙木 英行, 中川尚志, 永田里恵, Nozomu Matsumoto, 人工内耳パラメータフィッティングへの対比較ベース対話型差分進化の適用, 第6回 進化計算学会進化計算研究会, 2014.03, [URL].
51. 波多江晃一, 髙木 英行, 対話型差分進化ベースの動作姿勢生成支援システム, 第15回 日本知能情報ファジィ学会 九州支部学術講演会, 2013.12.
52. 裴岩, 髙木 英行, Method for determining search states of Markov Chain practically and its application to predict EC convergence and proof it, 2013進化計算シンポジウム, 2013.12.
53. PEI Yan, Takagi Hideyuki, Fitness Landscape Approximation by Adaptive Support Vector Regression with Opposition-Based Learning, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC 2013), 2013.10, We propose a method for approximating a fitness landscape using adaptive support vector regression (SVR) with opposition based learning (OBL) to enhance the evolutionary search. This method tries to resolve the complexity of the fitness landscape in the original search space by designing a suitable kernel function with an adaptive parameter tuned by OBL; This kernel projects the original search space into a higher dimensional search space with a different topological structure. The elite is obtained from the approximated fitness landscape, using the adaptive SVR to accelerate the evolutionary computation (EC) search, and the individual with the worst fitness is replaced. The merits of the proposed method are evaluated by comparing it with the fitness landscape approximated in the original, in a lower and in a higher dimensional search space.
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54. Takagi Hideyuki, Overview of Our Research on Interactive Evolutionary Computation, Japan-Finland Joint Seminar 2013, 2013.06, [URL], We summarize our research on interactive evolutionary computation (IEC) in this decade. Our major IEC research directions are (A) expanding IEC applications in new areas to show wide applicability of IEC, (B) reducing IEC user fatigue to make IEC more practical, (C) developing new IEC frameworks, and (D) analyzing human characteristics using IEC. Among them, we introduce some our recent works in (B) - (D): development of algorithms for accelerating EC search, paired comparison-based interactive differential evolution, IEC with evolutionary multi-objective optimization, and IEC for human science..
55. Takagi Hideyuki, Statistical Tests for Computational Intelligence Research and Human Subjective Tests, 2013 IEEE Symposium Series on Computational Intelligence, 2013.04, [URL], See at http://www.design.kyushu-u.ac.jp/~takagi/TAKAGI/StatisticalTests.html.
56. Takagi Hideyuki, Interactive evolutionary computation as a tool for human science, 九州大学芸術工学研究院応用知覚科学研究センター, 2013.04.
57. 髙木 英行, 裴岩, Exploration からExploitation への変化を加速する手法の提案, 第4回進化計算研究会, 2013.03.
58. 石津雅司, 髙木 英行, 「対話型差分進化を用いた地下鉄路線図の配色最適化に関する研究」, 福岡, pp.5-6 (2013年3月2日)., 第3回SOFT九州支部学生部会研究発表会, 2013.03.
59. PEI Yan, Takagi Hideyuki, Triple and Quadruple Comparison-Based Interactive Differential Evolution and Differential Evolution, Foundations of Genetic Algorithms XII (FOGA) 2013 Workshop, 2013.01.
60. PEI Yan, Takagi Hideyuki, Fitness Landscape Approximation by Adaptive Support Vector Regression with Opposition-Based Learning, Satellite Workshop on Problem, Landscape Analysis, Automated Algorithm Selection and Adaptation in Optimization at Foundations of Genetic Algorithms (FOGA2013) Workshop XII, 2013.01, [URL], We introduce two techniques to approximate and analyze fitness landscape for evolutionary search enhancement. One involves dimensionality reduction method used for fitness landscape approximation to reduce the computational complexity of the fitting. The other uses Fourier transform to obtain the frequency information of fitness landscape for search acceleration and multi-modal optimization. We briefly describe the inspirations, principles and results of the two techniques..
61. Anak Agung Gede Dharma, 髙木 英行, 富松 潔, Interactive neural network – Differential evolution framework for haptic feedback retrieval system, 進化計算シンポジウム2012, 2012.12.
62. 裴岩, 髙木 英行, 適応度景観の近似と解析による進化計算の探索能力の向上, 第14回日本知能情報ファジィ学会九州支部学術講演会, 2012.12.
63. PEI Yan, ZHENG Shaoqiu, TAN Ying, Takagi Hideyuki, An empirical study on influence of approximation approaches on enhancing fireworks algorithm, EEE Int. Conf. on Systems, Man, and Cybernetics (SMC 2012), 2012.10.
64. MA JingYe, 髙木 英行, Design of composite image filters using interactive genetic programming, 3rd Int. Conf. on Innovations in Bio-Inspired Computing and Applications, 2012.09.
65. 裴岩, 髙木 英行, 3 点および4 点比較ベースの対話型差分進化と差分進化
, 第3回進化計算研究会, 2012.09.
66. Takagi Hideyuki, Introduction to Computational Intelligence and Interactive Evolutionary Computation,, 2012 Cybernetics Summer School (CSS2012), 2012.08.
67. PEI Yan, Takagi Hideyuki, Comparative study on fitness landscape approximation with Fourier transform, 6th Int. Conf. on Genetic and Evolutionary Computing (ICGEC2012), 2012.08.
68. PEI Yan, Takagi Hideyuki, Fourier analysis of the fitness landscape for evolutionary search acceleration, 2012 IEEE Congress on Evolutionary Computation, 2012.06.
69. 馬菁野,高木英行, 対話型遺伝的プログラミングによる複合画像処理フィルタの設計, 第2回進化計算研究会・第8回進化計算フロンティア研究会合同研究会, 2012.03, [URL].
70. Sonny Alves Dias,猪口裕香,高木英行, Star Trek ゲームプレーヤ意思決定モデルの進化, 第2回進化計算研究会・第8回進化計算フロンティア研究会合同研究会, 2012.03, [URL].
71. 船木亮平,高木英行, IDE/gravity とIDE/moving vector の相補効果, 第2回進化計算研究会・第8回進化計算フロンティア研究会合同研究会, 2012.03, [URL].
72. 裴岩,高木英行, 多峰性最適化のためのフーリエ・ニッチ法, 第2回進化計算研究会・第8回進化計算フロンティア研究会合同研究会, 2012.03, [URL].
73. 船木亮平,高木英行, 対話型差分進化高速化手法DE/gravityの大局的最適解位置と収束特性との関係解析, 進化計算シンポジウム2011, 2011.12, [URL].
74. 裴岩,高木英行, 適応度景観のフーリエ解析による進化的探索高速化の試み, 進化計算シンポジウム2011, 2011.12, [URL].
75. Anak Agung Gede Dharma, 髙木 英行, 富松 潔, 対比較ベース対話型差分進化を用いた振動触覚メッセージの感性表現デザイン, 進化計算シンポジウム2011, 2011.12, [URL].
76. Yan Pei, 髙木 英行, Comparative evaluations of evolutionary computation with elite obtained in reduced dimensional spaces, 3rd International Conference on Intelligent Networking and Collaborative Systems (INCoS2011), 2011.11.
77. 高木英行, 対話型進化計算の高速化の取組と人間科学への応用, 電子情報通信学会技術研究報告 ニューロコンピューティング研究会 NC2011-5, 2011.10.
78. Yan Pei and Hideyuki Takagi, A Novel Traveling Salesman Problem Solution by Accelerated Evolutionary Computation with Approximated Cost Matrix in Industrial Application, 2nd International Conference of Soft Computing and Pattern Recognition (SoCPaR 2011), 2011.10.
79. Yan Pei and Hideyuki Takagi, A Survey on Accelerating Evolutionary Computation Approaches, 2nd International Conference of Soft Computing and Pattern Recognition (SoCPaR 2011), 2011.10.
80. 裴岩, 高木英行, 次元削減によって得られたエリートを用いた進化計算の高速化, 第1回進化計算研究会・第7回進化計算フロンティア研究会合同研究会, 2011.09.
81. Yan Pei and Hideyuki Takagi, Accelerating Evolutionary Computation with an Elite Obtained in Projected One-Dimensional Spaces, 5th International Conference on Genetic and Evolutionary Computing, , 2011.08.
82. Ryohei Funaki and Hideyuki Takagi, Acceleration Methods with a Gravity Vector and a Moving Vector for both Differential Evolution and Interactive Differential Evolution, 5th International Conference on Genetic and Evolutionary Computing, 2011.08.
83. 船木亮平, 高木英行, 個体群重心と個体群移動ベクトルを用いた差分進化と対話型差分進化の高速化, 第6回進化計算フロンティア研究会, 2011.03, [URL].
84. 船木亮平, 高木英行, 対話型差分進化の高速化手法の提案, 進化計算シンポジウム2010, 2010.12, [URL].
85. 井上誠,高木英行, 進化的多数目的最適化のための少数目的組合せの提案とその評価, 進化計算シンポジウム2010, 2010.12, [URL].
86. Makoto Inoue and Hideyuki Takagi, Proposal of F-F-Objective Optimization for Many Objectives and its Evaluation with a 0/1 Knapsack Problem, The Second World Congress on Nature and Biologically Inspired Computing (NaBIC2010), 2010.12, [URL].
87. 船木亮平, 高木英行, 対話型差分進化の高速化手法の提案, 2010年度電子情報通信学会九州支部学生会講演会, 2010.09.
88. Hideyuki Takagi, Recent Topics of Interactive Evolutionary Computation, 4th International Workshop on Soft Computing Applications (SOFA2010), 2010.07, [URL].
89. 井上誠, 高木英行, 建築間取り計画のための対話型進化的計算と進化的多目的最適化の組合せ, 第15回計算工学講演会, 2010.05.
90. 高木英行, Denis Pallez, 対比較ベース対話型差分進化, 第3回進化計算シンポジウム, 2009.12.
91. Hideyuki Takagi and Denis Pallez, Paired Comparison-based Interactive Differential Evolution, The first World Congress on Nature and Biologically Inspired Computing (NaBIC2009), 2009.12, [URL].
92. Hideyuki Takagi, New Frameworks of Interactive Evolutionary Computation, The 5th International Conference on Computational Intelligence and Applications (IWCIA2009), 2009.11, [URL].
93. Makoto Inoue and Hideyuki Takagi, EMO-based Architectural Room Planning, IEEE Systems, Man, and Cybernetics (SMC2009), 2009.10, [URL].
94. 井上誠, 高木英行, 進化的多数目的最適化のための少数目的組合せ, 平成21年度(第62回)電気関係学会九州支部連合大会, 2009.09.
95. 中野雄,高木英行, 対話型PSO, 第19回インテリジェントシステムシンポジウム (FAN2009), 2009.09, [URL].
96. 劉暢,高木英行, 並列IEC ユーザの評価特性の類似度と協調作業効率の関係, 第19回インテリジェントシステムシンポジウム (FAN2009), 2009.09, [URL].
97. Yu Nakano and Hideyuki Takagi, Influence of Quantization Noise in Fitness on the Performance of Interactive PSO, IEEE Congress on Evolutionary Computation (CEC2009), 2009.05, [URL].
98. 高木英行, IEC研究の最近の話題, 第2回進化計算シンポジウム, 2008.12.
99. Hideyuki Takagi, Interactive Evolutionary Computing for ICT Design, The First International Workshop on Information Network Design, 2008.12.
100. 井上誠, 高木英行, 空間配置生成手法と進化的多目的最適化手法を用いた建築間取り最適化 - 集合住宅における6部屋と住戸内廊下の配置 -, 日本建築学会・第31回情報・システム・利用・技術シンポジウム, 2008.12.
101. Hideyuki Takagi, New Topics from Recent Interactive Evolutionary Computation Researches, 12th Int. Conf. on Knowledge-Based Intelligent Information and Engineering Systems (KES2008), 2008.09.
102. Makoto Inoue and Hideyuki Takagi, Layout Algorithm for an EC-based Room Layout Planning Support System, IEEE Conference on Soft Computing in Industrial Applications (SMCia2008), 2008.06.
103. 高木英行, 視聴覚心理生理ベースの信号処理, 電子情報通信学会総合大会, 2008.03.
104. Jan Dolinsky, 高木英行, 自然さ学習による手書き文字合成, 電子情報通信学会総合大会, 2008.03.
105. 井上誠, 高木英行, 進化的空間計画のための計算幾何モデル, 電子情報通信学会総合大会, 2008.03.
106. Hideyuki Takagi, Directing the Emotions of Video Movie Viewers Using Interactive Evolutionary Computation based on Physiological Data, 2nd International Symposium on Design of Artificial Environments, 2007.12.
107. Kimio Shiraishi, Yoshihiro Kanazawa, Mutsumi Saito, Hideyuki Takagi and Toshifumi Sakata, Measurement of Tinnitus Using Interactive Evolutionary Computation, 2nd International Symposium on Design of Artificial Environments, 2007.12.
108. Jan Dolinsky and Hideyuki Takagi, RNN With a Recurrent Output Layer for Learning of Naturalness, 14th International Conference on Neural Information Processing (ICONIP2007), 2007.11.
109. Jan Dolinsky and Hideyuki Takagi, Synthesizing Handwritten Characters Using Naturalness Learning, 5th International Conference on Computational Cybernetics (ICCC2007), 2007.10.
110. Raffi R. Kamalian, Alice M. Agogino, and Hideyuki Takagi, Use of Interactive Evolutionary Computation with Simplified Modeling
for Computationally Expensive Layout Design Optimization, IEEE Congress on Computational Intelligence (CEC2007), 2007.09.
111. 中野雄,高木英行, 対話型PSOにおける評価値量子化ノイズの影響, インテリジェント・システム・シンポジウム(FANシンポジウム), 2007.08.
112. 杉野繁一,高木 英行, インタラクティブ進化的計算による室内照明環境デザイン, 第23回ファジィシステムシンポジウム, 2007.08.
113. Alexandra Melike Brintrup and Hideyuki Takagi, The Effect of User Interaction Mechanisms in Multi-objective IGA, Genetic and Evolutionary Computaion Conference (GECCO2007), 2007.07.
114. 高木英行, 映像視聴者の情動制御をめざして, 21世紀COEワークショップ「快適性への生理・心理的アプローチ」, 2007.06.
115. 中野雄,高木英行, 対話型群知能に関する研究, 第8回日本知能情報ファジィ学会九州支部学術講演会, 2006.12.
116. 李林甫, 高木英行, 長崎聖子, 中田俊史, 映像メディアの物理特徴量と視聴者生理特性の対応関係の解明, 第8回日本知能情報ファジィ学会九州支部学術講演会, 2006.12.
117. Raffi R. Kamalian, Alice M. Agogino, and Hideyuki Takagi, Interactive Evolutionary CAD System for MEMS Layout Synthesis, 2006 IEEE International Conference on Systems, Man, and Cybernetics, 2006.10.
118. Shinya Henmi, Shino Iwashita, and Hideyuki Takagi, Interactive Evolutionary Computation with Evaluation Characteristics of Multi-IEC Users, 2006 IEEE International Conference on Systems, Man, and Cybernetics, 2006.10.
119. 入江健介, 中田俊史, 中岡伊織, 李林甫, 高木英行, 映像メディア視聴者の情動制御のための物理特徴量の抽出, 第22回ファジィシステムシンポジウム, 2006.09.
120. 中岡伊織, 中田俊史, 入江健介, 李林甫, 長崎聖子, 高木英行, 映像ショットの切り替え速度に対する速度感モデルの構築, 第22回ファジィシステムシンポジウム, 2006.09.
121. 高木英行, 「好み,感性,経験,生理反応に基づく最適設計手法」, 21世紀COEプロジェクト東京研究発表会, 2006.08.
122. Raffi R. Kamalian, Reic Yeh, Ying Zhang, Alice M. Agogino, and Hideyuki Takagi, Reducing Human Fatigue in Interactive Evolutionary Computation through Fuzzy Systems and Machine Learning Systems, 2006 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE2006), 2006.07.
123. Shangfei Wang, Xufa Wang, and Hideyuki Takagi, User Fatigue Reduction by an Absolute Rating Data-trained Predictor in IEC, 2006 IEEE Congress on Evolutionary Computation (CEC2007), 2006.07.
124. Alexandra Melike Brintrup, Hideyuki Takagi, Jeremy Ramsden, Evaluation of Sequential, Multi-objective, and Parallel Interactive Genetic Algorithms for Multi-objective Floor Plan Optimisation, EvoWorkshop2006, 2006.04.
125. 高木英行, IECの情動制御とMEMS設計への応用と評価特性モデル導入によるIECユーザ疲労軽減, 電気学会進化技術応用調査専門委員会第4回研究会, 2006.03.
126. 近藤聡, 趙強福, 高木英行, モーフィング技術を用いた情報隠蔽手法, 電子情報通信学会技術研究報告, 2006.02.
127. 逸見真弥,岩下志乃,高木英行, 複数ユーザーの評価特性を内蔵するIEC実現に向けた実ユーザーの評価特性解析, 第7回日本知能情報ファジィ学会九州支部学術講演会, 2005.12.
128. 高木英行,入江健介,中田俊史, インタラクティブ進化計算と生理的解析に基づくマルチメディア視聴者の情動制御への取り組み, 第7回日本知能情報ファジィ学会九州支部学術講演会, 2005.12.
129. 田中信壽,高木英行, ニューラルネットによる個人性を導入したVR酔い対策システム, 第7回日本知能情報ファジィ学会九州支部学術講演会, 2005.12.
130. Raffi R. Kamalian,高木英行,Ying Zhang,Alice M. Agogino, インタラクティブ進化的計算に基づくMEMS設計手法, 第7回日本知能情報ファジィ学会九州支部学術講演会, 2005.12.
131. 逸見真弥, 村田忠彦, 高木英行, 複数ユーザの評価特性を内蔵するインタラクティブ進化計算 -- シミュレーション評価 --, 第21回ファジィシステムシンポジウム, 2005.09.
132. 岩下志乃, 王上飛, 高木英行, 評価尺度変換を用いたユーザ評価特性の学習効率化とその評価, 第21回ファジィシステムシンポジウム, 2005.09.
133. Raffi R. Kamalian, Ying Zhang, Hideyuki Takagi, and Alice M. Agogino, Evolutionary Synthesis of Micromachines Using Supervisory Multiobjective Interactive Evolutionary Computation, 4th International Conference on Machine Learning and Cybernetics (ICMLC 2005), 2005.08.
134. Abhishek Singh, Barbara Minsker, and Hideyuki Takagi, Interactive Genetic Algorithms for Inverse Groundwater Modeling: Issues with Human Fatigue and Prediction Models, World Water \& Environmental Resources Congress 2005, 2005.05.
135. Meghna Babbar, Barbara Minsker, and Hideyuki Takagi, Expert Knowledge in Long-Term Groundwater Monitoring Optimization Process: The Interactive Genetic Algorithm Perspective, World Water \& Environmental Resources Congress 2005, 2005.05.
136. Shangfei Wang and Hideyuki Takagi, Evaluation of User Fatigue Reduction Through IEC Rating-Scale Mapping, The Fourth IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology(WSTST2005),, 2005.05.
137. Hideyuki Takagi, Design and Measurement with Interactive Evolutionary Computation, The Fourth IEEE International Workshop on Soft Computing as Transdisciplinary Science and Technology (WSTST2005), 2005.05.
138. Hideyuki Takagi, Tomohiro Takahashi, Ken Aoki, Applicability of interactive evolutionary computation to mental health measurement, IEEE International Conference on Systems, Man, and Cybernetics (SMC2004), 2004.10, We show experimentally the applicability of interactive evolutionary computation (IEC) to a new application field, mental health measurement. We had 3 schizophrenics and 5 mentally healthy students design happy and sad impression computer graphics (CG) lighting images using IEC and asked other 33 students to evaluate the CG images using Scheffe’s method of paired comparison. Statistical tests of the evaluations showed that the range of emotional impressions perceived by the three schizophrenics between happy–sad was significantly narrower than that which was perceived by the mentally healthy students (p < 0.01). This experimental result implies that IEC has potential to contribute to psychiatry, and it also showed the possibility to expand IEC applicability beyond conventional system optimization and to a new area, mental health measurement.
Keywords: interactive evolutionary computation, schizophrenia, mental health measurement, CG lighting..
139. Hideyuki Takagi, Tomohiro Takahashi, and Ken Aoki, Applicability of interactive evolutionary computation to mental health measurement, IEEE International Conference on Systems, Man, and Cybernetics, 2004.10.
140. Hiroaki Nishino, Tsuneo Kagawa, Hideyuki Takagi, and Kouichi Utsumiya, A synthesized 3DCG contents generator using IEC framework, IEEE International Conference on Systems, Man, and Cybernetics, 2004.10.
141. Raffi Kamalian, Alice M. Agogino, and Hideyuki Takagi, The role of contraints and human interaction in evolving MEMS designs: microresonator case study, The 2004 ASME International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, 2004.09.
142. Meghna Babbar, Barbara Minsker, Hideyuki Takagi, Interactive Genetic Algorithm Framework for Long Term Groundwater Monitoring Design, World Water & Environmental Resources Congress 2004, 2004.06.
143. 賀川経夫, 西野浩明, 宇都宮孝一, Hideyuki Takagi, 「対話型進化計算を利用した3次元モデル作成の一手法, 第20回ファジィシステムシンポジウム, 2004.06, We propose a new 3D modeling method using deformation of real objects scanned by range finders. A 3D object obtained by the range finder is typically represented as a triangle mesh representation (a set of polygons) in the computer. First, we show a method for transforming such 3D polygon data into a 2D gray scale image format using Fourier series. Then, the proposed method allows users to easily perform some 3D geometric operations such as deformations, shape blending and texture mapping by editing and retouching the corresponding 2D image. A method called interactive evolutionary computation (IEC) is adapted to realize the method. The users can easily find a new 3D model easily..
144. Hideyuki Takagi, Interactive Evolutionary Computation, Genetic and Evolutionary Computation (GECCO2004), 2004.06.
145. Raffi Kamalian, Hideyuki Takagi, and Alice M. Agogino, Optimized Design of MEMS by Evolutionary Multi-objective Optimization with Interactive Evolutionary Computation, Genetic and Evolutionary Computation (GECCO2004), 2004.06.
146. Meghna Babbar, Barbara Minsker, Takagi Hideyuki, Interactive Genetic Algorithm Framework for Long Term Groundwater Monitoring Design, World Water & Environmental Resources Congress 2004, 2004.06.
147. 高木英行, 高橋智宏, 青木研, インタラクティブ進化計算による心の計測への応用可能性, 第20回ファジィシステムシンポジウム, 2004.06.
148. 賀川経夫, 西野浩明, 宇都宮孝一, 高木英行, 対話型進化計算を利用した3次元モデル作成の一手法, 第20回ファジィシステムシンポジウム, 2004.06.
149. 高橋智宏, 高木英行, 対話型進化計算を用いた統合失調症者の感情表現ダイナミックレンジの計測, 第38回作業療法学会, 2004.06.
150. Rudolf Jakvsa, and Hideyuki Takagi, Tuning of Image Parameters by Interactive Evolutionary Computation, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC2003), 2003.10.
151. Hiroaki Nishino, Tsuneo Kagawa, Masaki Hieda, Hideyuki Takagi, and Kouichi Utsumiya, An IEC-Based 3D Geometric Morphing System, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC2003), 2003.10.
152. 中野晶太, 高木英行, インタラクティブECを用いた医療画像強調処理, 第19回ファジィシステムシンポジウム, 2003.09.
153. Hideyuki Takagi, Humanized Computational Intelligence with Interactive Evolutionary Computation, Int. Conf. on Computational Cybernetics, 2003.08.
154. Rudolf Jakvsa, Shota Nakano, and Hideyuki Takagi, Image Filter Design with Interactive Evolutionary Computation, Int. Conf. on Computational Cybernetics, 2003.08.
155. Chris Wijns, Fabio Boschetti, Hideyuki Takagi, and Louis Moresi, Interactive Inverse Modelling for Non-Linear Earth Processes, 2003 International Union of Geophysics and Geodesy (IUGG2003), 2003.06.
156. Rudolf Jaksa and Hideyuki Takagi, Analysis and Evaluation for Interactive Evolutionary Computation-based Image Processing, MPSシンポジウム, 2003.01.
157. 中野晶太, 高木英行, インタラクティブECによる視覚ベースの信号処理の応用可能性, 第4回日本ファジィ学会九州支部学術講演会, 2002.12.
158. Hideyuki Takagi, Norimasa Hayashida, Interactive EC-based Signal Processing, 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL2002), 2002.11, We introduce new types of signal processing for which the characteristics of the signal processing filters are designed automatically by interactive evolutionary computation (IEC) based on human perception, such as hearing or vision. We first describe our existing works that use this approach, such as recovering distorted speech and hearing-aid fitting, as well as other related works in this field. Next, we evaluate the capabilities of visual-based image signal processing using IEC and compare it with conventional linear filters for the tasks of edge detection, high pass filtering, and horizontal / vertical component filtering. The experimental comparisons show that the performances of both methods are similar, which means that the new approach, without a priori knowledge on signal processing, is useful when signal processing users are not signal processing experts such as is the case in medical image processing or photo-retouch design..
159. Hideyuki Takagi and Norimasa Hayashida, Interactive EC-based Signal Processing, 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL2002), 2002.11.
160. 高木英行, インタラクティブ進化計算:進化的計算論の最適化能力と人間の評価能力の融合, 日本ファジィ学会評価問題研究会第7回曖昧な気持ちに挑むワークショップ, 2002.11.
161. Tadahiko Murata and Hideyuki Takagi, Analysis of Evolutionary Computation Research Through IEEE Conferences, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC2002), 2002.10.
162. Hiroaki Nishino, Hideyuki Takagi, Sato Saga, and Kouichi Utsumiya, A Virtual Modeling System for Intuitive 3D Shape Conceptualization, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC2002), 2002.10.
163. Kei Ohnishi and Hideyuki Takagi, Optimization Based on Competition and Evolution Among Searching, Joint 1st International Conference on Soft Computing and Intelligent Systems and 3rd International Symposium on Advanced Intelligent Systems (SCIE&ISIS2002), 2002.10.
164. Hideyuki Takagi, Humanized Computational Intelligence with Interactive Evolutionary Computation, 6th National Computer Science and Engineering Conference (NCSEC2002), 2002.10.
165. Hiroaki Nishino, Hideyuki Takagi, Sato Saga, and Kouichi Utsumiya, A Virtual Design System Empowered by Soft Computing Techniques, 8th International Conference on Virtual Systems and Multimedia (VSMM2002), 2002.09.
166. 村田忠彦, 高木英行, IEEE国際会議における進化的計算研究の現状, 第18回ファジィシステムシンポジウム, 2002.08.
167. 高木英行, 林田憲昌, IECによる視覚ベース信号処理, 第18回ファジィシステムシンポジウム, 2002.08.
168. 高木英行, 轟祐吉, 西野浩明, 恒藤智恵子, 青木研, 宇都宮孝一, IECベースの遠隔地CG教育システム, 第18回ファジィシステムシンポジウム, 2002.08.
169. 大西圭, 高木英行, 探索領域適応アルゴリズムと進化アルゴリズムの組合せ, 第18回ファジィシステムシンポジウム, 2002.08.
170. Hideyuki Takagi, Introduction of Interactive Evolutionary Computation and Its Applications to Computer Graphics, the Sixth International Conference on Neural Network and Soft Computing, 2002.06.
171. 大崎美穂, 高木英行, 藤井成清, 坂本真一, 林田憲昌, 渡辺政博, IECフィッティング: 提案,システム開発,評価,そして今後の聴覚障害補償研究に向けて, 音響学会聴覚研究会, 2002.01.
172. 轟 祐吉, 恒藤智恵子, 高木英行, 西野浩明, 宇津宮孝一, and 青木 研, コンピュータグラフィックスのためのインタラクティブ進化計算, 第3回日本ファジィ学会九州支部学術講演会, 2001.12.
173. 大西 圭, 高木英行, 演繹的および帰納的方法論に基づく拡張進化計算, 第3回日本ファジィ学会九州支部学術講演会, 2001.12.
174. 藤井成清, 林田憲昌, 高木英行, 大崎美穂, PDA版 Visualized IECフィッティングシステム, 第3回日本ファジィ学会九州支部学術講演会, 2001.12.
175. Hideyuki Takagi, Interactive Evolutionary Computation as Humanized Computational Intelligence Technology, International Conference on Computational Intelligence (7th Fuzzy Days), 2001.10.
176. Hiroaki Nishino, Hideyuki Takagi, and Kouichi Utsumiya, Implementation and Evaluation of an IEC-Based 3D Modeling System, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC2001), 2001.10.
177. Chris Wijns, Louis Moresi, Fabio Boschetti, and Hideyuki Takagi, Inversion in Geology by Interactive Evolutionary Computation, IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC2001), 2001.10.
178. 林田憲昌, 高木英行, 適合度空間のランドスケープ可視化とユーザの能動的探索による進化計算の高速化, MPSシンポジウム(進化的計算シンポジウム), 2001.10.
179. 西野浩明, 高木英行, 宇都宮孝一, 対話型進化計算と幾何モデラによる相補型デザインシステムの試作と評価, MPSシンポジウム(進化的計算シンポジウム), 2001.10.
180. 大西圭,高木英行, 探索点生成メカニズムの進化に基づく最適化, MPSシンポジウム(進化的計算シンポジウム), 2001.10.
181. 藤井成清, 高木英行, 動的聴覚障害補償特性実現のための予備的検討, 日本音響学会九州支部第4回学生のための講演会, 2001.10.
182. Miho Ohsaki, Shin'ich Sakamoto, Hideyuki Takagi, Development and Evaluation of an IEC Fitting System for Hearing Aids, Int'l Conf. on Acoustics (ICA2001), 2001.09.
183. Dilip Kumar Pratihar, Norimasa Hayashida, and Hideyuki Takagi, Comparison of Mapping Methods to Visualize the EC Landscape, 5th Int. Conf. on Knowledge-Based Intelligent Information Engineering Systems & Allied Technologies (KES2001), 2001.09.
184. 大崎美穂, 坂本真一, 高木英行, IECフィッティングの実用性の評価, 日本ファジィ学会東海支部主催, 第11回東海ファジィ研究会, 2001.09.
185. 高木英行, 轟祐吉, 対話的な魚CG生成と魚の自立分散的な行動モデルに関する研究, 第6回日本バーチャルリアリティ学会全国大会, 2001.09.
186. 西野浩明, 高木英行, 宇都宮孝一, 発想支援型3次元モデラの試作と評価, 第6回日本バーチャルリアリティ学会全国大会, 2001.09.
187. Hideyuki Takagi, Computational Intelligence for Geo-science, Workshop on Future Direction in the Analysis of Potential Field Data: Inversion, Signal Processing, Interpretation, 2001.08.
188. Hideyuki Takagi, Advancing the Human Experience with Interactive Evolutionary Computation, IEEE Mountain Workshop on Soft Computing in Industrial Application (SMCia/01), 2001.06.
189. Fabio Boschetti and Hideyuki Takagi, Visualization of EC Landscape to Accelerate EC Conversion and Evaluation of its Effect, IEEE Congress on Evolutionary Computation (CEC2001), 2001.05.
190. 西野浩明,高木英行,宇都宮孝一, 対話型進化計算を用いた3次元造形システム, 情報処理学会九州支部主催「火の国情報シンポジウム2001」, 2001.03.
191. Hiroaki Nishino, Hideyuki Takagi, Sung-Bae Cho, Kouichi Utsumiya, A 3D Modeling System for Creative Design, The 15th International Conference on Information Networking (ICOIN-15), 2001.01.
192. Hiroaki Nishino, Hideyuki Takagi, Sung-Bae Cho, and Kouichi Utsumiya, A 3D Modeling System for Creative Design, The 15th Int'l Conf. on Information Networking (ICOIN-15), 2001.01.
193. 西野浩明,高木英行,宇都宮孝一, 対話型進化計算による3次元モデル制作支援機構, 電子情報通信学会 信学技報, 2000.11.
194. Norimasa Hayashida, Hideyuki Takagi, Visualized IEC: Interactive Evolutionary Computation with Multidimensional Data Visualization, IEEE International Conference on Industrial Electronics, Control and Instrumentation (IECON2000), 2000.10.
195. Hiroaki Nishino, Hideyuki Takagi, Kouichi Utsumiya, A Digital Prototyping System for Designing Novel 3D Geometries, 6th International Conference on Virtual Systems and MultiMedia (VSMM2000), 2000.10.
196. Yukichi Todoroki and Hideyuki Takagi, User Interface of an Interactive Evolutionary Computation for Speech Processing, 6th Int'l Conf. on Soft Computing (IIZUKA2000), 2000.10.
197. Toshihiko Noda, Dong Zhao, and Hideyuki Takagi, Music Database Retrieval and Media Conversion System Based on Impression, 6th Int'l Conf. on Soft Computing (IIZUKA2000), 2000.10.
198. Shigekiyo Fujii, Hideyuki Takagi, Miho Ohsaki, Masahiro Watanabe, and Shin'ichi Sakamoto, Evaluation and Analysis of IEC Fitting, 7th Western Pacific Regional Acoustics Conference (WESTPRAC VII), 2000.10.
199. Kei Ohnishi and Hideyuki Takagi, Feed-Back Model Inspired by Biological Development to Hierarchically Design Complex Structure, IEEE Int'l Conf. on System, Man, and Cybernetics (SMC2000), 2000.10.
200. Norimasa Hayashida and Hideyuki Takagi, Visualized IEC: Interactive Evolutionary Computation with Multidimensional Data Visualization, IEEE Int'l Conf. on Industrial Electronics, Control and Instrumentation (IECON2000), 2000.10.
201. Toshihiko Noda, Dong Zhao, Hideyuki Takagi, Music Database Retrieval and Media Conversion System Based on Impression, 6th International Conference on Soft Computing (IIZUKA2000), 2000.10.
202. 木村明大,岩崎勤,北島律之,高木英行,竹田仰, インタラクティブ進化計算による魚形成ソフトの開発, 電気関係学会九州支部連合会大会, 2000.09.
203. 岩崎勤,木村明大,轟祐吉,広瀬勇一郎,高木英行,竹田仰, ユーザ参加型バーチャル水族館(第1報), 日本バーチャルリアリティ学会第5回大会, 2000.09.
204. Hideyuki Takagi and Miho Ohsaki, IEC Fitting: New framework of hearing aid fitting based on computational intelligence technology and user's preference for hearing, Poster session PB9, Int'l Hearing Aid Research Conference (IHCON2000), 2000.08.
205. Hideyuki Takagi, Computational Intelligence with Human Capability, International Symposium on Computational Intelligence (ISCI2000), 2000.08.
206. Miho Ohsaki and Hideyuki Takagi, Design and Development of an IEC-based Hearing Aids Fitting System, 4th Asia Fuzzy System Symposium (AFSS'00), 2000.05.
207. Hiroaki Nishino, Hideyuki Takagi, and Kouichi Utsumiya, A Digital Prototyping System for Designing Novel 3D Geometries, 6th Int'l Conf. on Virtual Systems and MultiMedia (VSMM2000), 2000.04.
208. 大崎美穂, 高木英行, 渡辺政博, 坂本真一, IECフィッティングシステムの実用化 - 従来式補聴器への適用 -, 日本音響学会講演論文集 2-10-1, 2000.03.
209. Hideyuki Takagi, Active User Intervention in an EC Search, International Conference on Information Sciences (JCIS2000,), 2000.02.
210. Hideyuki Takagi, Active User Intervention in an EC Search, Int'l Conf. on Information Sciences (JCIS2000), 2000.02.
211. 渡辺政博, 坂本真一, 大崎美穂, 高木英行, 対話型進化計算手法を用いた補聴器フィッティングシステムの開発, 日本音響学会聴覚研究会 H-2000-6, 2000.01.
212. 藤井 成清, 高木英行, 大崎 美穂, 新居 康彦, IECフィッティング技術に基づく聴覚補償上の知見獲得, 日本音響学会聴覚研究会, 1999.12.
213. 野田 寿彦, 趙東, 高木英行, 寺岡章人, 印象に基づくメディアデータベース検索およびメディア変換システム, 日本ファジィ学会九州支部大会, 1999.12.
214. 轟祐吉,高木英行, 音声処理におけるインタラクティブ進化計算のユーザーインターフェイス, 日本ファジィ学会九州支部大会, 1999.12.
215. 林田憲昌, 高木英行, 多次元データの2次元視覚化によるインタラクティブ進化計算への能動選択機能の導入, 日本ファジィ学会九州支部大会, 1999.12.
216. 大西圭,高木英行, 発生生物学に基づく生成アルゴリズムの提案, 日本ファジィ学会九州支部大会, 1999.12.
217. Hideyuki Takagi, Miho Ohsaki, IEC-based Hearing Aids Fitting, IEEE International Conference on System, Man, and Cybernetics (SMC'99), 1999.10.
218. Hideyuki Takagi, Toshihiko Noda, Sung-Bae Cho, Psychological Space to Hold Impression Among Media in Common for Media Database Retrieval System, IEEE International Conference on System, Man, and Cybernetics (SMC'99), 1999.10.
219. Hideyuki Takagi, Takashi Takeda, Chin-Huat Ewe, Moving Model of a CG Head and Its Parametric Expression of Gender and Age, IEEE Int'l Conf. on System, Man, and Cybernetics (SMC'99), 1999.10.
220. Hideyuki Takagi and Miho Ohsaki, IEC-based Hearing Aids Fitting, IEEE Int'l Conf. on System, Man, and Cybernetics (SMC'99), 1999.10.
221. Hideyuki Takagi, Toshihiko Noda, and Sung-Bae Cho, Psychological Space to Hold Impression Among Media in Common for Media Database Retrieval System, IEEE Int'l Conf. on System, Man, and Cybernetics (SMC'99), 1999.10.
222. 高木英行, 感性に基づくシステム自動最適化技術:アート、工学から アミューズメント応用へ, 福岡産学ジョイントプラザ'99, 1999.10.
223. Hideyuki Takagi and Katsuhiro Kishi, On-line Knowledge Embedding for Interactive EC-based Montage System, Third International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES'99), 1999.09.
224. Hideyuki Takagi, Katsuhiro Kishi, On-line Knowledge Embedding for Interactive EC-based Montage System, Third International Conference on Knowledge-Based Intelligent Information Engineering Systems (KES'99), 1999.08.
225. Hideyuki Takagi, Sung-Bae Cho, Toshihiko Noda, Evaluation of an IGA-based Image Retrieval System Using Wavelet Coefficients, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'99), 1999.08.
226. Takeo Ingu, Hideyuki Takagi, Accelerating a GA Convergence by Fitting a Single-Peak Function, IEEE International Conference on Fuzzy Systems (FUZZ-IEEE'99), 1999.08.
227. Hideyuki Takagi, Sung-Bae Cho, Toshihiko Noda, Evaluation of an IGA-based Image Retrieval System Using Wavelet Coefficients, IEEE Int'l Conf. on Fuzzy Systems (FUZZ-IEEE'99), 1999.08.
228. Takeo Ingu and Hideyuki Takagi, Accelerating a GA Convergence by Fitting a Single-Peak Function, IEEE Int'l Conf. on Fuzzy Systems (FUZZ-IEEE'99), 1999.08.
229. Hideyuki Takagi, Shin'ichi Kamohara, Takashi Takeda, Introduction of Soft Computing Techniques to Welfare Equipment, 1999 IEEE Midnight-Sun Workshop on Soft Computing Methods in Industrial Applications (SMCia'99), 1999.06.
230. Hideyuki Takagi, Shin'ichi Kamohara, and Takashi Takeda, Introduction of Soft Computing Techniques to Welfare Equipment, 1999 IEEE Midnight-Sun Workshop on Soft Computing Methods in Industrial Applications (SMCia'99), 1999.06.
231. 大崎美穂、高木英行, 対話型EC組み込み補聴器フィッティングシステム の構築と評価, 第15回ファジィシステムシンポジウム, 1999.06.
232. 岸 克洋、高木英行, インタラクティブ進化計算におけるオンライン 知識組み込みの評価, 第15回ファジィシステムシンポジウム, 1999.06.
233. 野田寿彦、高木英行、張明智, 画像検索のための心理因子空間構成と 対話型GAベース画像検索システムの主観評価, 第15回ファジィ システムシンポジウム, 1999.06.
234. 印具毅雄、高木英行, 単峰性関数当てはめによるGA高速化の評価, 第15回ファジィシステムシンポジウム, 1999.06.
235. 高木英行,大崎美穂, 聴覚障害者の聴こえに基づく聴覚補償の自動最適化, 日本音響学会講演論文集 1-2-18, 1999.03.
236. 大崎美穂,津村尚志,高木英行,島田真弓, IECフィティングシステムの 音声聴取に対する評価, 日本音響学会講演論文集 1-2-19, 1999.03.
237. 大崎美穂,津村尚志,高木英行,島田真弓, IECフィティングシステムの 音楽聴取への応用, 日本音響学会講演論文集 1-2-20, 1999.03.
238. 岸克洋,高木英行, 対話型進化的計算研究ツールとしてのモンタージュシステムの開発, 日本ファジィ学会第3回曖昧な気持ちに挑むワークショップ, 1998.11.
239. Hideyuki Takagi, Interactive Evolutionary Computation - Cooperation of computational intelligence and human KANSEI -, 5th International Conference on Soft Computing (IIZUKA'98), 1998.10, In this paper, we overview Interactive EC (evolutionary computation) research, showing the status quo and its remaining problems. The interactive EC technique optimizes systems from human interaction with computers. Recently, interest in this approach has increased in many application elds that we categorize into the artistic, engineering, and educational elds. We then overview the research within each eld. Finally, we show several trials to address the problem of human fatigue.
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240. Miho Ohsaki and Hideyuki Takagi, Improvement of Presenting Interface by Predicting the Evaluation Order to Reduce the Burden of Human Interactive EC Operators, IEEE Int'l Conf. on System, Man, Cybernetics (SMC'98), 1998.10.
241. Hideyuki Takagi, Interactive Evolutionary Computation - Cooperation of computational intelligence and human KANSEI -, 5th Int'l Conf. on Soft Computing (IIZUKA'98), 1998.10.
242. Miho Ohsaki and Hideyuki Takagi, Application of Interactive Evolutionary Computation to Optimal Tuning of Digital Hearing Aids, 5th Int'l Conf. on Soft Computing (IIZUKA'98), 1998.10.
243. 尤振発,高木英行,竹田仰, CG顔像の振り向き方における性差および 年齢差の表現, 電気関係学会九州支部連合会大会, 1998.10.
244. Hideyuki Takagi, Interactive Evolutionary Computation: System Optimization Based on Human Subjective Evaluation, IEEE International Conference on Intelligent Engineering Systems (INES'98), 1998.09.
245. Hideyuki Takagi, Interactive Evolutionary Computation: System Optimization Based on Human Subjective Evaluation, IEEE Int'l Conf. on Intelligent Engineering Systems (INES'98), 1998.09.
246. Miho Ohsaki, Hideyuki Takagi, Takeo Ingu, Methods to Reduce the Human Burden of Interactive Evolutionary Computation, Asia Fuzzy System Symposium (AFSS'98), 1998.06.
247. 大崎美穂, 高木英行, ディジタル補聴器フィッティングへの対話型ECの応用, 第14回ファジィシステムシンポジウム, 1998.06.
248. 高木英行,青木研, インタラクティブEC:創造支援から工学応用へ, ワークショップ「インタラクティブ進化的計算論」, 1998.03.
249. 高木英行,大崎美穂,印具毅雄, インタラクティブEC操作者の疲労軽減手法, ワークショップ「インタラクティブ進化的計算論」, 1998.03.
250. Shin'ichi Kamohara, Hideyuki Takagi, and Takashi Takeda, Control Rule Acquisition for an Arm Wrestling Robot, IEEE Int'l Conf. on System, Man, Cybernetics (SMC'97), 1997.10.
251. 青木研, 高木英行, 3次元CGにおけるライティングデザイン支援, 第13回ファジィシステムシンポジウム, 1997.06.
252. 印具毅雄, 高木英行,大崎美穂, 対話型遺伝的アルゴリズムのインタ フェース改善 −GAの高速化手法の提案−, 第13回ファジィシステム シンポジウム, 1997.06.
253. Ken Aoki, Hideyuki Takagi, 3-D CG Lighting with an Interactive GA, 1st International Conference on Conventional and Knowledge-based Intelligent Electronic Systems (KES'97), 1997.05.
254. Ken Aoki, Hideyuki Takagi, 3-D CG Lighting with an Interactive GA, 1st Int. Conf. on Conventional and Knowledge-based Intelligent Electronic Systems (KES'97), 1997.05.
255. 竹田 仰, 高木英行, CG人物像の視線移動のための頭部と眼球の動きモデル, 電報通信学会総合大会, 1997.03.
256. 青木研, 高木英行, 対話型GAによる3次元CGライティング設計支援, 電報通信学会総合大会, 1997.03.
257. Hideyuki Takagi,Kimiko Ohya,Miho Ohsaki, Improvement of Input Interface for Interactive GA and its Evaluation, Int'l Conf. on Soft Computing (IIZUKA'96), 1996.10.
258. Ken Aoki,Hideyuki Takagi, Naomi Fujimura, Interactive GA-based Design Support System for Lighting Design in Computer Graphics, Int'l Conf. on Soft Computing (IIZUKA'96), 1996.10.
259. Hideyuki Takagi, Interactive GA for System Optimization: Problems and Solution, 4th European Congress on Intelligent Techniques and Soft Computing (EUFIT'96), 1996.09.
260. Hideyuki Takagi, System Optimization Without Numerical Target, 1996 Biennial Conference of the North American Fuzzy Information Processing Society (NAFIPS'96), 1996.06.
261. 高木英行, 大宅喜美子, 大崎美穂, 対話型遺伝的アルゴリズムのインタフェース改善手法の提案と評価, 第12回ファジィシステムシンポジウム, 1996.06.
262. 蒲原新一, 高木英行, 竹田 仰, 仮想現実感を与える腕相撲制御ルールの獲得, 第12回ファジィシステムシンポジウム, 1996.06.
263. Hideyuki Takagi,Kimiko Ohya, Discrete Fitness Values for Improving the Human Interface in an Interactive GA, IEEE 3rd Int'l Conf. on Evolutionary Computation (ICEC'96), 1996.05.
264. Hideyuki Takagi, Industrial and Commercial Applications of NN/FS/GA/Chaos in 1990s, Int'l Workshop on Soft Computing in Industry (IWSCI'96), 1996.04.
265. 竹田 仰, 高木英行, ノンバーバルインタフェースのための頭部と視線の 動きの推定, 第38回ヒューマンインタフェース研究会, 1996.04.
266. 高木英行, 大宅喜美子, 対話型GAの入力インタフェース改善方法とその評価, 電子情報通信学会総合大会, 1996.03.
267. 高木英行, 知的処理のためのニューラルネット/ファジィ/遺伝的アルゴリズム, 第21回歯科人工知能研究会・第5回日本コンピュータ歯科医学会共催大会, 1996.01.
268. Eiji Mizutani, Jyh-Shing R. Jang, Kenichi Nishio, Hideyuki Takagi, and David M. Auslander, Coactive Neuro-Fuzzy Modeling for Color Recipe Prediction, IEEE Int'l Conf. on Neural Networks (ICNN'95), 1995.12.
269. Eiji Mizutani, Hideyuki Takagi, and David M. Auslander, Evolving Color Paint, IEEE Int'l Conf. on Evolutionary Computation (ICEC'95), 1995.11.
270. Tatsumi Watanabe, Hideyuki Takagi, Recovering System of the Distorted Speech using Interactive genetic Algorithms, IEEE International Conference on Systems, Man and Cybernetics (SMC'95), 1995.10.
271. Tatsumi Watanabe and Hideyuki Takagi, Recovering System of the Distorted Speech using Interactive genetic Algorithms, IEEE Int'l Conf. on Systems, Man and Cybernetics (SMC'95), 1995.10.
272. Hideyuki Takagi, Auto-Designing Systems Based on Soft Computing Techniques and Human Preference, 3rd European Congress on Intelligent Techniques and Soft Computing (EUFIT'95), 1995.08.
273. 渡辺辰巳, 高木英行, 対話型GAを用いた歪音声の音質の改善, 第11回ファジィ・システム・シンポジウム, 1995.07.
274. Mika Sato, Lakhmi C. Jain, and Hideyuki Takagi, Design and Implementation of Knowledge-Based Intelligent Systems, 1995.05.
275. Takeshi Furuhashi, Hideyuki Takagi, and Lakhmi C. Jain, Intelligent Systems Using Artificial Neural Networks, Fuzzy Logic, and Genetic Algorithms in Industry, 1995.05.
276. Eiji Mizutani, Hideyuki Takagi, and David M. Auslander, A Cooperative System based on Soft Computing Methods to Realize Higher Precision of Computer Color Recipe Prediction, 1995.04.
277. Eiji Mizutani, Jyh-Shing R. Jang, Kenichi Nishio, Hideyuki Takagi, and David M. Auslander, Coactive Neural Networks with Adjustable Fuzzy Membership Functions and Their Applications, Int'l Conf. on Fuzzy Logic, Neural Networks, and Soft Computing (IIZUKA'94), 1994.08.
278. Michael H. Smith and Hideyuki Takagi, Fuzzy Approximators: Optimizing a Fuzzy System by Dynamically Tuning the Ratio of Firing Strengths, Int'l Conf. on Fuzzy Logic, Neural Networks, and Soft Computing (IIZUKA'94), 1994.08.
279. Masao Ozaki, Michael A. Lee, and Hideyuki Takagi, Neural Network, Fuzzy System, and Multiple Regression Models for Dental Age Prediction, Int'l Conf. on Fuzzy Logic, Neural Networks, and Soft Computing (IIZUKA'94), 1994.08.
280. Eiji Mizutani, Hideyuki Takagi, and David M. Auslander, A Cooperative System of Neural Networks and Genetic Algorithm with Fuzzy Population Generator for Computer Recipe Prediction, Int'l Conf. on Fuzzy Logic, Neural Networks, and Soft Computing (IIZUKA'94), 1994.08.
281. Michael A. LEE and Hideyuki Takagi, Learning Control Strategies for High Performance Genetic Algorithms, 1994 IEEE/Nagoya University World Wiesemen/women Workshop on Fuzzy Logic and Neural Networks/Genetic Algorithms (WWW'94) - Architecture and Applications for Knowledge Acquisition/Adaptation, 1994.08.
282. 高木英行, ニューラルネット/ファジィ/GAの融合化と産業への応用, 電気学会産業応用部門全国大会, 1994.08.
283. 高木英行, ファジィシステムのための遺伝的アルゴリズムと、遺伝的 アルゴリズムためのファジィシステム, 第2回関西情報関連学会連合大会, 1994.07.
284. 高木英行, ファジィシステムのためのGAと、GAのためのファジィ システム, 日本工業技術振興協会、遺伝的アルゴリズム研究委員会第6会定例会, 1994.01.
285. Hideyuki Takagi, Fusion techniques of fuzzy systems and neural networks, and fuzzy systems and genetic algorithms, SPIE Proc. of Technical Conf. on Applications of Fuzzy Logic Technology, SPIE's Int'l Symposium on Optical Tools for Manufacturing and Advanced Automation, 1993.09.
286. Thomas Hessburg, Michael A. Lee, Hideyuki Takagi, and Masao Tomizuka, Automatic design of fuzzy systems using genetic algorithms and its application to lateral vehicle guidance, SPIE Proc. of Technical Conf. on Applications of Fuzzy Logic Technology, SPIE's Int'l Symposium on Optical Tools for Manufacturing and Advanced Automation, 1993.09.
287. Hideyuki Takagi, Michael H. Smith, Optimization of Fuzzy Systems by Switching Reasoning Methods Dynamically, 5th IFSA World Congress, 1993.07.
288. Hideyuki Takagi,Michael A. Lee, Embedding Apriori Knowledge into an Integrated Fuzzy System Design Method Based on Genetic Algorithms, 5th IFSA World Congress, 1993.07.
289. Michael A. Lee and Hideyuki Takagi, Optimization of Fuzzy Systems by Switching Reasoning Methods Dynamically, 5th IFSA World Congress, 1993.07.
290. Michael A. Lee and Hideyuki Takagi, Dynamic Control of Genetic Algorithms using Fuzzy Logic Techniques, Proc. of 5th Int'l Conf. on Genetic Algorithms (ICGA'93), 1993.07.
291. Hideyuki Takagi and Michael A. Lee, Neural Networks and Genetic Algorithm Approaches for Auto-Design of Fuzzy Systems, 8th Austrian Artificial Intelligence Conference - Fuzzy Logic in Artificial Intelligence (FLAI'93), 1993.06.
292. Michael A. Lee and Hideyuki Takagi, Integrating Design Stage of Fuzzy System using Genetic Algorithms, IEEE 2nd Int'l Conf. on Fuzzy Systems (FUZZ-IEEE'93), 1993.04.
293. Hideyuki Takagi, Integrating Design Stage of Fuzzy System using Genetic Algorithms, IEEE 2nd International Conference on Fuzzy Systems (FUZZ-IEEE'93), 1993.03, This paper proposes an automaticfuzzy system design method that uses a Genetic Algorithm and integrates three design stages; our method determines membership functions, the number of fuzzy rules, and the ruleconsequent parameters at the same time. Because these design stages may not be independent, it is important to consider them simultaneously to obtain optimal fuzzy systems. The method includes a genetic algorithm and a penalty strategy that favors systems with fewer rules. The proposed method is applied to the classic inverted pendulum control problem and has been shown to be practical through a comparison with another method..
294. Hideyuki Takagi, Application of neural networks and fuzzy logic to consumer products, IEEE Int'l Conf. on Industrial Electronics, Control, Instrumentation, and Automation (IECON'92), 1992.11.
295. Hideyuki Takagi, Using Boundary Shape Data for Effective Adaptive Rule Modifications, 2nd Int'l Conf. on Fuzzy Logic & Neural Networks (IIZUKA'92), 1992.07.
296. Hideyuki Takagi, Design of Fuzzy System by NNs and Realization of Adaptability, 3rd Int'l Workshop on Neural Networks and Fuzzy Logic, 1992.06.
297. Hideyuki Takagi, Cooperative System of Neural Networks and Fuzzy Logic and its Applications, Cooperative System of Neural Networks and Fuzzy Logic and its Applications, 1992.01.
298. Hideyuki Takagi, Cooperative System of Neural Networks and Fuzzy Logic and Its Application to Consumer Products, 1st Int'l Workshop on Industrial Applications of Fuzzy Control and Intelligent Systems, 1991.11.
299. 目片強司,吉住嘉之,山田義則,高木英行, ニューラルネットワークを 用いた雑音抑圧, 日本音響学会講演論文集 3-7-5, 1991.10.
300. 目片強司,吉住嘉之,山田義則,高木英行, ニューラルネットワークと 聴覚フィルタバンクを用いた雑音抑圧, 電子情報通信学会秋季全国大会, 1991.09.
301. Hideyuki Takagi and Noriyuki Suzuki, Application of neural-network design on approximate reasoning architecture to the adjustment of VTR tape-running mechanisms, 4th IFSA World Congress, 1991.07.
302. 高木英行, 民生機器への展開 −NNへの論理の組み込み−, SYNAPSE'91 (Symposium on Neural-networks; Alliance and Perspective in Senri) パネルディスカッション, 1991.05.
303. Kazuaki Obara and Hideyuki Takagi, Formant extraction model by neural networks and auditory model based on signal processing theory, Int'l Conf. on Spoken Language Processing (ICSLP-90),, 1990.11.
304. 高木英行,小原和昭, 聴覚末梢系の準同形処理的解釈とホルマント抽出 モデル, 日本音響学会聴覚研究会資料 H-90-55, 1990.11.
305. Hideyuki Takagi, Fusion of fuzzy system and neural networks, and its strong points and problems, Sino-Japan Joint Meeting on Fuzzy Sets and Systems, 1990.10.
306. 小島良宏,香田敏行,高木英行,〆木泰治, ニューラルネットワークの 汎化性に関する一検討, 電子情報通信学会秋季全国大会 D-5, 1990.10.
307. 高木英行,小原和昭, 仮説機能を含む聴覚モデルと、ニューラルネット によるホルマント抽出, 日本音響学会講演論文集 1-7-16, 1990.09.
308. 中橋順一, 坪香英一, 高木英行, スペクトルの動的特徴を考慮した HMMによる不特定話者数字認識, 日本音響学会講演論文集 1-8-20, 1990.09.
309. 高木英行, ニューラルネットとファジィの融合化 - NN→ファジィ・ファジィ→NN -, 関西情報センター 第5回人工知能 研究会, 1990.09.
310. Hideyuki Takagi, Fusion technology of fuzzy theory and neural networks -- Survey and future directions --, Int'l Conf. on Fuzzy Logic & Neural Networks (IIZUKA-90), 1990.07.
311. Hideyuki Takagi, Toshiyuki Kouda, and Yoshinori Kojima, Neural-network designed on approximate reasoning architecture and its application to the pattern recognition, 1st Int'l Conf. on Fuzzy Logic & Neural Networks (IIZUKA'90), 1990.07.
312. 鈴木良二,三崎正之,高木英行, 聴覚末梢系モデルを用いた雑音 抑圧方式, 電子情報通信学会春季全国大会 A-253, 1990.03.
313. 中橋順一, 坪香英一, 高木英行, スペクトルの動的特徴を考慮した HMMによる日本語音韻の識別, 日本音響学会講演論文集 2-P-25, 1990.03.
314. 中橋順一, 坪香英一, 高木英行, 調音結合部における動的特徴を 加味したHMMの評価, 日本音響学会講演論文集 1-1-19, 1989.11.
315. 香田敏行, 阪上茂生, 山本浩司, 高木英行, 〆木泰治, 誤差適応型 評価関数によるバックプロパゲーション学習法の高速化, 電子情報通信学会秋季全国大会D-208, 1989.09.
316. 阪上茂生, 高木英行, 香田敏行, 山本浩司, 〆木泰治, ニューラル ネットによる画像符号化の学習の高速化, 電子情報通信学会秋季全国大会 D-209, 1989.09.
317. 高木英行, 知的システムを目指す − ニューラルネット・ファジィ 推論・エキスパートシステムの融合 −, 第2回東海AI研究会・情報処理学会中部支部講演会共催, 1989.07.
318. Hideyuki Takagi, Introduction of fast neural network algorithm and artificial_neural_network-driven fuzzy reasoning into seismology, Sino-Japan Conf. on Seismological Research, 1989.05.
319. 香田敏行, 阪上茂生, 高木英行, 〆木泰治, ニューラルネットによる 手書き英数字認識 −計算量の削減および学習の高速化に関する検討−, 電子情報通信学会パターン認識研究会, RTU88-151, 1989.03.
320. 坪香英一, 高木英行, 音声スペクトルの動的特徴を反映したHMMと その有効性, 日本音響学会講演論文集 1-6-17, 1989.03.
321. 高木英行, 阪上茂生, 戸川隼人, 非線形最適化手法を用いたニューラル ネットワーク学習アルゴリズムの高速化, 電子情報通信学会春季全国大会 SD-1-12, 1989.03.
322. 阪上茂生, 高木英行, 香田敏行, 〆木泰治, 戸川隼人, ニューラルネットワークの学習における非線形最適化手法の評価検討, 電子情報通信学会春季全国大会 SD-1-13, 1989.03.
323. 高木英行, ニューラルネットからのエキスパートシステムへの アプローチ, 土木学会関西支部共同研究グループ「土木工学へのエキスパート システム適用に関する調査研究」第4回共同研究会, 1989.01.
324. 高木英行, パネル討論: 知的システムへのアプローチ −ニューラル ネットの立場から −, IFSA日本支部関西地区定例研究会, IFSA日本支部ファジィ推論とエキスパートシステム研究会, 情報処理学会関西支部システムソルビング研究会, CAI学会関西支部 共催, 1988.12.
325. 高木英行, 坪香英一, ニューラルネットによる音韻セグメンテーション, 日本音響学会講演論文集 2-P-7, 1988.10.
326. 高木英行, 林勲, ニューラルネット駆動型ファジィ推論, 電子情報通信学会秋季全国大会, 1988.09.
327. 香田敏行, 高木英行, 〆木泰治, ニューラルネットによる手書き 英数字認識−モデル規模と学習データによる検討−, 電子情報通信学会パターン認識研究会, PRU88-57, 1988.09.
328. 林勲, 野村博義, 高木英行, 長坂一徳, ニューラルネット駆動型 ファジィ推論の提案, シンポジウム「あいまい情報処理と知的システム制御」 (計測自動制御学会関西支部主催), 1988.09.
329. 高木英行, ニューラルネットの音声・画像・制御への応用, マイクロエレクトロニクス研究開発機構第2回大阪ワークショップ 「ニューラルコンピュータ」, 1988.09.
330. Hideyuki Takagi and Isao Hayashi, Artificial_neural_network-driven fuzzy reasoning, Int'l Workshop on Fuzzy System Applications (IIZUKA'88), 1988.08.
331. 林勲, 高木英行, 推論規則を自己獲得するニューラルネット駆動型 ファジィ推論, 第14回システム・シンポジウム(計測自動制御学会主催), 1988.08.
332. 林勲, 高木英行, 神経回路網モデルによるファジィ推論の定式化, 第4回ファジィ・システム・シンポジウム(IFSA日本支部主催), 1988.05.
333. 高木英行, 坪香英一, ニューラルネットを用いた擬似ホルマント抽出 フィルタリング, 日本音響学会講演論文集 3-P-11, 1988.03.
334. 高木英行, 原紀代, ニューラルネットを用いたプロソディーの制御 −ピッチの制御について−, 日本音響学会講演論文集 3-P-12, 1988.03.
335. 坪香英一, 高木英行, 原紀代, 動的特徴を加味した音韻パターンの表現 の一方法, 日本音響学会講演論文集 3-3-6, 1987.10.
336. 三宮真智子, 高木英行, 樺澤哲, 三尾忠男, 主観評価実験による音声 入力とキー入力との比較, 日本音響学会講演論文集 3-5-10, 1987.03.
337. Machiko Sannomiya, Satoshi Kabasawa, Hideyuki Takagi, and Atushi Yoshiya, A study on voice recognition as human interface for Japanese word-processor, 2nd Symposium on Human Interface, 1986.10.
338. 樺澤哲, 原紀代, 高木英行, 坪香英一, 文節音声データベースの作成, 日本音響学会講演論文集 1-3-10, 1986.10.
339. 高木英行, 樺澤哲, 坪香英一, 日本語統計情報による音韻識別, 日本音響学会講演論文集 2-3-18, 1986.10.
340. 高木英行, 音声入力ワードプロセッサの主観評価, 第2回ヒューマン・インタフェース・シンポジウム, 1986.10.
341. 高木英行, 楠原久代, 坪香英一, 音声日本語文入力における日本語統計 情報の評価, 日本音響学会講演論文集 1-1-25, 1986.03.
342. 高木英行, 楠原久代, 坪香英一, 音節連鎖情報の音声認識誤り訂正性能, 電子通信学会総合全国大会 1387, 1986.03.
343. 樺澤哲, 高木英行, 正しい音声入力を得るためのガイダンスの検討, 第1回ヒューマン・インタフェース・シンポジウム, 1985.10.
344. 樺澤哲, 高木英行, 正しい音声入力のためのガイダンス手法の検討, 日本音響学会講演論文集 2-4-12, pp.73-74, 1985.09.
345. 高木英行, 中嶋章子, 楠原久代, 前原文雄, 日本語統計情報の音声 認識への応用, 日本音響学会講演論文集 1-4-21, pp.41-42, 1985.03.
346. 伊達玄, 高木英行, 線形予測分析によるハウリング防止の検討, 日本音響学会講演論文集1-4-21, pp.257-258, 1981.10.
347. 高木英行, 小西孝明, 福留公利, 伊達玄, 音響信号の二次元変換記録 再生方式における再生歪みの検討(窓によるセグメント化), 日本音響学会 講演論文集 1-5-13, pp.207-208, 1979.06.

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