云遗传算法

戴朝华; 朱云芳; 陈维荣

云遗传算法

详细信息

作者简介:
戴朝华(1974- ),男,博士研究生,研究方向为计算智能、多目标优化等,E-mail:dchzyf@126.com;陈维荣(1965- ),男,教授,博士生导师,主要研究方向为综合自动化、智能检测技术,E mai:l w rchen@home.swjtu.edu.cn

戴朝华(1974- ),男,博士研究生,研究方向为计算智能、多目标优化等,E-mail:dchzyf@126.com;陈维荣(1965- ),男,教授,博士生导师,主要研究方向为综合自动化、智能检测技术,E mai:l w rchen@home.swjtu.edu.cn

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出版历程
- 收稿日期: 2005-09-28
- 刊出日期: 2006-12-25

Cloud Theory-Based Genetic Algorithm

摘要

摘要: 为了克服传统遗传算法搜索速度慢、易陷入局部最优解的缺陷,借鉴遗传算法的思想,利用云模型云滴的随机性和稳定倾向性的特点,提出了一种新的遗传算法——云遗传算法(CGA).该算法由正态云模型的Y条件云发生器实现交叉操作,由基本云发生器实现变异操作.最后,进行了函数优化实验,并与标准遗传算法(SGA)和自适应遗传算法(AGA)进行了比较,以证明其有效性.
- 遗传算法 /
- 云理论 /
- 云遗传算法 /
- 函数优化
Abstract: To overcome the shortcomings of a genetic algorithm(GA).i.e.,low convergence speed and easily getting a local optimum solution,a novel genetic algorithm,cloud theory-based genetic algorithm(CGA),was proposed.CGA is based on both the idea of GA and the properties of randomness and stable tendency of a normal cloud model.In this algorithm,Y-conditional cloud generator is used as the cross operator,and basic cloud generator as the mutation operator.Finally,an experiment of function optimization was carried out and a comparison with standard genetic algorithm(SGA) and adaptive genetic algorithm(AGA) was made to testify the validity of CGA,the proposed genetic algorithm.
- genetic algorithm /
- cloud theory /
- cloud genetic algorithm /
- function optimization

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参考文献(1)

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文章访问数: 1789
HTML全文浏览量: 74
PDF下载量: 423
被引次数: 0

云遗传算法

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出版历程

Cloud Theory-Based Genetic Algorithm

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出版历程

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