Optimizing Parameters of Fuzzy Petri Net Based on Artificial Immune Algorithm

Abstract:

Aiming at knowledge reasoning ability of fuzzy petri net depending on the parameter and the parameters usually obtained by specialist, an algorism based on artificial immune algorism for obtaining the optimum parameters was proposed. Firstly, the fuzzy petri net and generating rules were defined and described, and then the coding method of antibody, Affinity evaluation function and Simulated Annealing immune selection operator are designed to improve the classic artificial immune algorism. The specific algorism based on this improved artificial algorism was defined. The simulation experiment shows the method in this paper can accurately realize the parameters optimizing and has the litter square error, compared with the other methods, our method has the quick global convergence rate, optimizing ability and strong Versatility.

• Periodical: Advanced Materials Research (Volumes 756-759)
• Pages: 3389-3393
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.756-759.3389
• Online since: September 2013
• Authors: Bai Ming Liu, Ai Qin Qi, Wei Wei
• Keywords: Artificial Immune, Component, Fuzzy, Parameter Optimizing, Petri Net

References

[1] Wang yuying, chenping. Combination Timed Colored Petri Net-based Web service modeling, Computer Science, 2010, PP: 152-155.

[2] Calin Ciufudean, Adrian Graur, Constantin Filote, etc. A new Formalism for Failure Diagnosis: Ant Colony Decision Petri Nets . Journal of software, 2007, PP: 39-46.

DOI: 10.4304/jsw.2.1.39-46

[3] P.F. Palamara, V. A. Ziparo, L. Iocchi, et al. A Robotic Soccer Passing Task Using Petri Net Plans [J]. In Proc. of 7th Int. Conf. on Autonomous Agents and Multi-agent Systems, 2008, PP : 1711-1712.

DOI: 10.1007/s10458-010-9146-1

[4] Fang huwang, Wang hongqiang. rete stochastic optimal control conditions Markov structure. Control Theory and Applications, 2010, pp: 99-102.

[5] Xiao zhengliang. Parameter optimization algorithm based on ant colony - genetic algorithm fuzzy Petri nets. Computer Technology and Application，2010, pp: 33-35.

[6] Yang jinsong. hybrid intelligent algorithm to optimize the parameters of fuzzy Petri net . Computer Applications and Software, 2010, pp: 169-172.

[7] Zhan wenhui. Based on the study of the genetic algorithm-BP the FPN parameter optimization. Computer Engineering, 2008, pp: 252-254.

[8] Li YANG. icial fish swarm algorithm FPN parameter optimization [J], Computer Engineering, 2006, pp: 189-191.

[9] H. Meng, X. Zhang and S. Liu A novel clonal selection for multi-modal function optimization, ICNC (2), 2006, PP. 63-72.