Parameter optimization of fuzzy neural networks based on cultural quantum- behaved particle swarm optimization

Computer Engineering and Applications ›› 2011, Vol. 47 ›› Issue (10): 17-19.

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Parameter optimization of fuzzy neural networks based on cultural quantum- behaved particle swarm optimization

ZHAO Jing1，2，SUN Jun1，XU Wenbo1

1.School of Internet of Things Engineering，Jiangnan University，Wuxi，Jiangsu 214122，China
2.Center of Modern Education Technology，Shandong Polytechnic University，Jinan 250353，China

Received:1900-01-01 Revised:1900-01-01 Online:2011-04-01 Published:2011-04-01

基于文化量子粒子群的模糊神经网络参数优化

赵晶1，2，孙俊1，须文波1

1.江南大学物联网工程学院，江苏无锡 214122
2.山东轻工业学院现代教育技术中心，济南 250353

Abstract

Abstract: The parameter optimization of Fuzzy Neural Network（FNN） is function optimization.According to the low convergence precision of the existed algorithms，a hybrid Cultural Quantum-behaved Particle Swarm Optimization（C-QPSO） is introduced to train the parameter optimization of FNN.The results of experiment show the proposed technique is effective.

Key words: Fuzzy Neural Network（FNN）, parameter optimization, Quantum-behaved Particle Swarm Optimization（QPSO）, Cultural Algorithm（CA）, chaotic time series

摘要： 模糊神经网络参数学习是一个函数优化问题。针对已有优化方法收敛精度不高的缺点，提出基于文化量子粒子群算法的模糊神经网络参数优化，并将其应用于混沌时间序列预测。仿真实例结果证实了该算法的优越性。

关键词: 模糊神经网络, 参数优化, 量子粒子群算法, 文化算法, 混沌时间序列

ZHAO Jing1，2，SUN Jun1，XU Wenbo1. Parameter optimization of fuzzy neural networks based on cultural quantum- behaved particle swarm optimization[J]. Computer Engineering and Applications, 2011, 47(10): 17-19.

赵晶1，2，孙俊1，须文波1. 基于文化量子粒子群的模糊神经网络参数优化[J]. 计算机工程与应用, 2011, 47(10): 17-19.

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Parameter optimization of fuzzy neural networks based on cultural quantum- behaved particle swarm optimization

基于文化量子粒子群的模糊神经网络参数优化

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