计算机工程与应用2011，Vol.47Issue(15)：39-42,93,5.DOI:10.3778/j.issn.1002-8331.2011.15.011
克隆选择算法在优化模糊Petri网参数中的应用
Research on cional selection algorithm applied in parameters optimization of fuzzy Petri nets
摘要
Abstract
It is significant and being unsolved yet for building a Fuzzy Petri Net(FPN) to determine all parameters of fuzzy production rules. In this paper, Clonal Selection Algorithm(CSA) is originally introduced into the procedure of exploring parameters of FPN.An optimization algoritnm based on the techniques of multithreading is proposed. Realization of the algorithm hasn't depended on experiential data and requirements for primary input are not critical. Simulation experiment shows that the trained parameters gained from above CSA are highly accurate and the resultant FPN model possesses strong generalizing capability and self-adjusting purpose.关键词
模糊Petri网/模糊推理/克隆选择算法/线程技术Key words
Fuzzy Petri Net(FPN)/fuzzy reasoning/Clonal Selection Algorithm(CSA)/multithreading分类
信息技术与安全科学引用本文复制引用
李洋,乐晓波..克隆选择算法在优化模糊Petri网参数中的应用[J].计算机工程与应用,2011,47(15):39-42,93,5.基金项目
湖南省教育厅自然科学基金资助项目(No.01JJY2061) （No.01JJY2061）
湖南省教育厅科研基金资助项目(No.01C306). （No.01C306）
