Title :
A hybrid of cooperative particle swarm optimization and cultural algorithm for neural fuzzy networks
Author :
Chen, Cheng Hung ; Liu, Yong Cheng ; Cheng-Jian Lin ; Lin, Chin Teng
Author_Institution :
Dept. of Electr. & Control Eng., Nat. Chiao-Tong Univ., Hsinchu
Abstract :
This study presents an evolutionary neural fuzzy network, designed using the functional-link-based neural fuzzy network (FLNFN) and a new evolutionary learning algorithm. This new evolutionary learning algorithm is based on a hybrid of cooperative particle swarm optimization and cultural algorithm. It is thus called cultural cooperative particle swarm optimization (CCPSO). The proposed CCPSO method, which uses cooperative behavior among multiple swarms, can increase the global search capacity using the belief space. Cooperative behavior involves a collection of multiple swarms that interact by exchanging information to solve a problem. The belief space is the information repository in which the individuals can store their experiences such that other individuals can learn from them indirectly. The proposed FLNFN model uses functional link neural networks as the consequent part of the fuzzy rules. Finally, the proposed functional-link-based neural fuzzy network with cultural cooperative particle swarm optimization (FLNFN-CCPSO) is adopted in several predictive applications. Experimental results have demonstrated that the proposed CCPSO method performs well in predicting the time series problems.
Keywords :
cooperative systems; evolutionary computation; fuzzy neural nets; particle swarm optimisation; belief space; cultural algorithm; cultural cooperative particle swarm optimization; evolutionary learning algorithm; evolutionary neural fuzzy network; functional link neural networks; functional-link-based neural fuzzy network; fuzzy rules; Cultural differences; Fuzzy neural networks; Fuzzy systems; Particle swarm optimization;
Conference_Titel :
Fuzzy Systems, 2008. FUZZ-IEEE 2008. (IEEE World Congress on Computational Intelligence). IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1818-3
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZY.2008.4630371