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基于递阶遗传算法的模糊系统优化设计
引用本文:马铭,周春光,张利彪,窦全胜.基于递阶遗传算法的模糊系统优化设计[J].吉林大学学报(理学版),2004,42(4):599-564.
作者姓名:马铭  周春光  张利彪  窦全胜
作者单位:1. 吉林大学计算机科学与技术学院, 长春 130012; 2. 北华大学计算中心,吉林 132013
基金项目:国家自然科学基金(批准号:60175024),教育部科学技术研究重点项目基金(批准号:02090).
摘    要:给出一种基于递阶遗传算法的模糊神经网络优化算法, 在该算法中对每个染色体都采用递阶编码, 并提出一种改进的交叉算子, 可以同时优化模糊神经网络结构和权值参数. 算法中采用双目标函数作为适应度函数对模糊神经网络模型的精确度和复杂性进行估价, 且对应一个实际问题, 可以通过调整适应度函数的参数值确定所需模糊神经网络模型的精确度和复杂性之间的比例, 从而生成一个适当的模糊神经网络模型. 模拟实验结果验证了该算法的有效性.

关 键 词:递阶遗传算法  模糊神经网络  优化  
文章编号:1671-5489(2004)04-0559-06
收稿时间:2004-04-14
修稿时间:2004年4月14日

Optimization of fuzzy system based on hierarchical genetic algorithm
MA Ming.Optimization of fuzzy system based on hierarchical genetic algorithm[J].Journal of Jilin University: Sci Ed,2004,42(4):599-564.
Authors:MA Ming
Institution:1. College of Computer Science and Technology, Jilin University, Changchun 130012, China; 2. Computer Center, Beihua University, Jilin 132013, China
Abstract:Based on the deep study of fuzzy neural networks and hierarchical genetic algorithm, an algorithm is proposed to optimize fuzzy neural network. In the proposed algorithm, the hierarchical coding is adopted to each chromosome, and an improved crossover operater is proposed, so it can evolve both the fuzzy neural network's topology and weighting parameters. Furthermore, a two-objective function is used as fitness fuction to (evaluate) the structure complexity and the performance of the fuzzy neural networks, and we can confirm the proportion between the complexity and the performance by changing the value of the parameter for a given problem, then we can obtain the near-optimal fuzzy neural network architecture for the problem. Numerical simulations showed the effectiveness of the proposed algorithm.
Keywords:hierarchical genetic algorithm  fuzzy neural network  optimize
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