Fuzzy Petri net parameter optimization algorithms based on ant-colony-inherit algorithm

doi:10.3778/j.issn.1002-8331.2010.29.009

Computer Engineering and Applications ›› 2010, Vol. 46 ›› Issue (29): 33-35.DOI: 10.3778/j.issn.1002-8331.2010.29.009

• 研究、探讨 • Previous Articles Next Articles

Fuzzy Petri net parameter optimization algorithms based on ant-colony-inherit algorithm

XIAO Zeng-liang，YUE Xiao-bo，ZHOU Hui

College of Computer & Communication Engineering，Changsha University of Science & Technology，Changsha 410076，China

Received:2010-05-13 Revised:2010-08-19 Online:2010-10-11 Published:2010-10-11
Contact: XIAO Zeng-liang

基于蚁群-遗传算法的模糊Petri网参数优化算法

肖增良，乐晓波，周辉

长沙理工大学计算机与通信工程学院，长沙 410076

通讯作者: 肖增良

Abstract

Abstract: In the process of establishing fuzzy Petri net，how to determine the parameters of fuzzy production rules is a hot issue which is yet to be resolved.This paper proposes a GAACA algorithm which combines ant colony algorithm with genetic algorithm.Simulation results show that this algorithm has strong generalization ability and adaptive capability which can achieve the purpose of parameter optimization.

摘要： 在模糊Petri 网（FPN）的建立过程中如何确定模糊产生式规则的各项参数是尚未解决的热点问题。将蚁群算法和遗传算法相结合，提出了GAACA算法。仿真实验表明：该算法具有很强的泛化能力和自适应功能，能够达到参数优化的目的。

CLC Number:

TP301

XIAO Zeng-liang，YUE Xiao-bo，ZHOU Hui. Fuzzy Petri net parameter optimization algorithms based on ant-colony-inherit algorithm[J]. Computer Engineering and Applications, 2010, 46(29): 33-35.

肖增良，乐晓波，周辉. 基于蚁群-遗传算法的模糊Petri网参数优化算法[J]. 计算机工程与应用, 2010, 46(29): 33-35.

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Fuzzy Petri net parameter optimization algorithms based on ant-colony-inherit algorithm

基于蚁群-遗传算法的模糊Petri网参数优化算法

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