中国电子科技(英文版)2003，Vol.1Issue(1)：63-68,6.
A New Neuro-Fuzzy Adaptive Genetic Algorithm
A New Neuro-Fuzzy Adaptive Genetic Algorithm
ZHU Lili 1ZHANG Huanchun 1JING Yazhi1
作者信息
- 1. Faculty 302, Nanjing University of Aeronautics and Astronautics, Nanjing 210016 China
- 折叠
摘要
Abstract
Novel neuro-fuzzy techniques are used to dynamically control parameter settings of genetic algorithms (GAs). The benchmark routine is an adaptive genetic algorithm (AGA) that uses a fuzzy knowledge-based system to control GA parameters. The self-learning ability of the cerebellar model ariculation controller(CMAC) neural network makes it possible for on-line learning the knowledge on GAs throughout the run. Automatically designing and tuning the fuzzy knowledge-base system, neurofuzzy techniques based on CMAC can find the optimized fuzzy system for AGA by the renhanced learning method. The Results from initial experiments show a Dynamic Parametric AGA system designed by the proposed automatic method and indicate the general applicability of the neuro-fuzzy AGA to a wide range of combinatorial optimization.关键词
genetic algorithm/fuzzy logic control/CMAC neural network/adaptive parameter controlKey words
genetic algorithm/fuzzy logic control/CMAC neural network/adaptive parameter control分类
信息技术与安全科学引用本文复制引用
ZHU Lili,ZHANG Huanchun,JING Yazhi..A New Neuro-Fuzzy Adaptive Genetic Algorithm[J].中国电子科技(英文版),2003,1(1):63-68,6.
