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摘要:
Optimization implies the minimization or maximization of an objective function. Some problems have sev-eral optimum points which all, should be computed. Niching method is presented to do so. However, its efficiency can be improved via combining it with Memetic algorithm. Therefore, in this paper, Memetic method is used to improve this method in terms of convergence rate and diversity. In the proposed methods, genetic algorithm, PSO, and learning automata are used as a local search algorithm of Memetic method. The result of simulations demonstrates that proposed methods are more effective compared with Niching in terms of convergence and diversity.
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篇名 Using Intelligent Computational Methods for Optimizing Niching Method
来源期刊 智能科学国际期刊(英文) 学科 数学
关键词 PSO NICHING GENETIC Algorithm LEARNING AUTOMATA
年,卷(期) 2011,(1) 所属期刊栏目
研究方向 页码范围 1-7
页数 7页 分类号 O1
字数 语种
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研究主题发展历程
节点文献
PSO
NICHING
GENETIC
Algorithm
LEARNING
AUTOMATA
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引文网络交叉学科
相关学者/机构
期刊影响力
智能科学国际期刊(英文)
季刊
2163-0283
武汉市江夏区汤逊湖北路38号光谷总部空间
出版文献量(篇)
102
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0
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