Optimizing Quantitative and Qualitative Objectives by User-System Cooperative Evolutionary Computation for Image Processing Filter Design

Author:

Ono Satoshi,Maeda Hiroshi,Sakimoto Kiyomasa,Nakayama Shigeru

Publisher

Springer International Publishing

Reference18 articles.

1. Amamiya, A., Miki, M., Hiroyasu, T.: Interactive genetic algorithm using initial individuals produced by support vector machine. In: The Science and Engineering Review of Doshisha University, vol. 50, no. 1, pp. 34–45 (2009)

2. Ando, D., Iba, H.: Interactive composition aid system by means of tree representation of musical phrase. In: Proceedings of the IEEE Congress on Evolutionary Computation, pp. 4258–4265 (2007)

3. Hitoyasu, T., Kobayashi, Y., Sasaki, Y., Tanaka, M., Miki, M., Yoshimi, M.: Discussion of evaluation methods for multiobjective interactive genetic algorithm. In: Proceedings of the World Automation Congress, CD-ROM (2010)

4. Horn, J.: The nature of niching: genetic algorithms and the evolution of optimal cooperative populations, p. 97008. Technical report IlliGAL Report No (1997)

5. Huang, W., Matsushita, D., Munemoto, J.: Interactive evolutionary computation (IEC) method of interior work (iw) design for use by non-design-professional Chinese residents. J. Asian Arch. Build. Eng. 5(1), 91–98 (2006). http://ci.nii.ac.jp/naid/110004773753/en/

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