Optimizing Parameters of Fuzzy Petri Net Based on Artificial Immune Algorithm
- 10.2991/iccia.2012.255How to use a DOI?
- component,Parameter optimizing, artificial immune, Petri Net, fuzzy
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.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Baiming Liu AU - Aiqin Qi AU - Wei Wei PY - 2014/05 DA - 2014/05 TI - Optimizing Parameters of Fuzzy Petri Net Based on Artificial Immune Algorithm BT - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012) PB - Atlantis Press SP - 1040 EP - 1043 SN - 1951-6851 UR - https://doi.org/10.2991/iccia.2012.255 DO - 10.2991/iccia.2012.255 ID - Liu2014/05 ER -