一種新的模糊遺傳算法

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一種新的模糊遺傳算法

李擎, 鄭德玲, 唐勇, 陳占英

文章導航 > 工程科學學報 > 2001 > 23(1): 85-89

李擎, 鄭德玲, 唐勇, 陳占英. 一種新的模糊遺傳算法[J]. 工程科學學報, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

引用本文:

李擎, 鄭德玲, 唐勇, 陳占英. 一種新的模糊遺傳算法[J]. 工程科學學報, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

LI Qing, ZHENG Deling, TANG Yong, CHEN Zhanying. A New Kind of Fuzzy Genetic Algorithm[J]. Chinese Journal of Engineering, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

Citation:

LI Qing, ZHENG Deling, TANG Yong, CHEN Zhanying. A New Kind of Fuzzy Genetic Algorithm[J]. Chinese Journal of Engineering, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

李擎, 鄭德玲, 唐勇, 陳占英. 一種新的模糊遺傳算法[J]. 工程科學學報, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

引用本文:

李擎, 鄭德玲, 唐勇, 陳占英. 一種新的模糊遺傳算法[J]. 工程科學學報, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

LI Qing, ZHENG Deling, TANG Yong, CHEN Zhanying. A New Kind of Fuzzy Genetic Algorithm[J]. Chinese Journal of Engineering, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

Citation:

LI Qing, ZHENG Deling, TANG Yong, CHEN Zhanying. A New Kind of Fuzzy Genetic Algorithm[J]. Chinese Journal of Engineering, 2001, 23(1): 85-89. doi: 10.13374/j.issn1001-053x.2001.01.050

一種新的模糊遺傳算法

doi: 10.13374/j.issn1001-053x.2001.01.050

1. 北京科技大學信息工程學院, 北京 100083;
2. 冶金部自動化研究院, 北京 100071

基金項目:

國家自然科學基金（No.69772014）

作者簡介:
李擎男,29歲,博士

中圖分類號: TP273⁺.4
計量
- 文章訪問數: 200
- HTML全文瀏覽量: 29
- PDF下載量: 8
- 被引次數: 0
出版歷程
- 收稿日期: 2000-06-18

A New Kind of Fuzzy Genetic Algorithm

1. Information Engineering School, UST Beijing, Beijing 100083, China;
2. Automation Research Institute of the Ministry of Metallurgical Industry Beijing 100071, China

摘要: 將模糊控制思想引人到遺傳算法中,進行交叉概率P_c和變異概率P_m的整定工作,并在此基礎上提出了一種基于模糊控制的遺傳算法——模糊遺傳算法.仿真結果表明:該算法不僅能提高解的質量,而且能加速解的收斂速度.
- 遺傳算法 /
- 模糊控制 /
- 交叉概率 /
- 變異概率
Abstract: The fuzzy control method is mixed into the genetic algorithm to adjust the probabilities of crossover and mutation. A new improved genetic algorithm named the fuzzy genetic algorithm (FGA) is proposed. Simulation results show that FGA is very efficiency for the quality of the solution is improved and the convergent speed of the solution is accelerated.
- genetic algorithm /
- fuzzy control /
- crossover probability /
- mutation probability

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PDF下載量: 8
被引次數: 0

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