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	An intelligent particle swarm optimization for designing trading-ratio system of water market
	Liu Y. ; Huang J. K. ; Wu Y. H. ; Liu B. ; Wang L. ; Jin Y. H.
	2006
关键词	networks
英文摘要	As a novel optimization technique, neural network based optimization has gained much attention and some applications during the past decade. To enhance the performance of particle swarm optimization (PSO), which is an evolutionary computation technique through individual improvement plus population cooperation and competition, an intelligent particle swarm optimization algorithm (IPSO) is proposed by incorporating differential evolution (DE) and neural network based search behaviors into classic PSO. Firstly, PSO and DE operators are simultaneously used for exploration by updating particle swarm so as to maintain the diversity of swarms and speedup the search process. Secondly, a multi-layer feed-forward neural network is employed for local exploitation to avoid being trapped in local optima and improve the convergence of the IPSO. Simulation results and comparisons based on well-known benchmarks and optimal designing of trading-ratio system for water market demonstrate that the IPSO can effectively enhance the searching efficiency and greatly improve the searching quality.
出处	Ecological Research
卷	13E
页	1757-1761
收录类别	SCI
语种	英语
ISSN号	1492-8760
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/25443]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Liu Y.,Huang J. K.,Wu Y. H.,et al. An intelligent particle swarm optimization for designing trading-ratio system of water market. 2006.

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