Title :
Differential evolution algorithem design for fuzzy neural network
Author :
Ma, Ming ; Sun, Yan ; Zhang, Li-Biao
Author_Institution :
Inf. Manage Center, Beihua Univ., Jilin, China
Abstract :
Differential evolution is a novel method to search global optimum. A new pruning algorithm for solving the fuzzy neural network design problem is proposed based on differential evolution with division of work. Based on the proposed algorithm, an optimal and efficient fuzzy neural network structure can be constructed by the requirements. Numerical simulations show the effectiveness of the proposed algorithm.
Keywords :
evolutionary computation; fuzzy neural nets; differential evolution algorithem design; fuzzy neural network; fuzzy neural network structure; optimum search; Algorithm design and analysis; Brain modeling; Evolutionary computation; Fuzzy neural networks; Machine learning; Optimization; Signal processing algorithms; Differential evolution; Fuzzy neural network; Fuzzy rule;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580834
