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自适应基因遗传算法及其在知识获取中的应用
引用本文:张雪江,朱向阳,钟秉林,黄仁.自适应基因遗传算法及其在知识获取中的应用[J].系统工程与电子技术,1997(7).
作者姓名:张雪江  朱向阳  钟秉林  黄仁
作者单位:东南大学机械工程系!南京210018
基金项目:国家重点自然科学基金,江苏省应用基础基金资助课题
摘    要:本文针对基因遗传算法中杂交率和变异率的难以选取问题,提出了一种自适应基因遗传算法.该方法利用降半Г分布函数对杂交率和变异率进行自适应调整,以保证群体的多样性和进化过程的稳定性,克服算法的未成熟收敛问题.最后以故障诊断知识获取为例,阐述该方法的有效性.

关 键 词:遗传算法  知识获取  应用

Adaptive Genetic Algorithm and Its Application to Knowledge Acquisition
Zhang Xuejiang,Zhu Xiangyan,Zhong Binglin and Huang Ren.Adaptive Genetic Algorithm and Its Application to Knowledge Acquisition[J].System Engineering and Electronics,1997(7).
Authors:Zhang Xuejiang  Zhu Xiangyan  Zhong Binglin and Huang Ren
Institution:Zhang Xuejiang,Zhu Xiangyan,Zhong Binglin and Huang Ren Department of Mechanical Engineering,Southeast University,Nanjing 210018
Abstract:In this paper, an adaptive genetic algorithm is proposed to solve the problem of choosing the probabilities of crossover and mutation. A special function is defined to adptively adjust the above two parameters, which garantees the diversity and stability of genetic algorithm and avoids its premature convergence. Application examples of diagnostic knowlege acquisition de-mostrate that the proposed approach is more effective than standard genetic algorithm.
Keywords:Genetic algorithm  Crossover probability  Mutation probability  Knowledge acquisition    
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