A METHOD OF IMPROVING PERFORMANCE OF FUZZY NEURAL NETWORK BASED ON DIFFERENTIAL EVOLUTION

摘要：

Differential evolution is a powerful evolutionary inspired search technique for global optimization. We have proposed a new algorithm based on differential Evolution to solve the fuzzy neural network design problem, it can identify an optimal and efficient fuzzy neural network structure for a given problem. Numerical simulations show the effectiveness of the proposed algorithm.

关键词： Differential evolution Fuzzy neural network Fuzzy rale

作者: MING MA YAN XU LI-BIAO ZHANG

作者单位: Information Manage Center, Beihua University, Jilin 132013, China College of Computer Science and Technology, Jilin University, Changchun 130012 , China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 874-877

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）