Abstract: This paper proposes a novel adaptive group organization cooperative evolutionary algorithm (AGOCEA) for TSK-type neural fuzzy networks design. The proposed AGOCEA uses group-based cooperative evolutionary algorithm and self-organizing technique to automatically design neural fuzzy networks. The group-based evolutionary divided populations to several groups and each group can evolve itself. In the proposed self-organizing technique, it can automatically determine the parameters of the neural fuzzy networks, and therefore some critical parameters have no need to be assigned in advance. The simulation results are shown the better performance of the proposed algorithm than the other learning algorithms.

Sheng-Fuu Lin and Jyun-Wei Chang, “Adaptive Group Organization Cooperative Evolutionary Algorithm for TSK-type Neural Fuzzy Networks Design” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 2(3), 2013. http://dx.doi.org/10.14569/IJARAI.2013.020301

@article{Lin2013,
title = {Adaptive Group Organization Cooperative Evolutionary Algorithm for TSK-type Neural Fuzzy Networks Design},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2013.020301},
url = {http://dx.doi.org/10.14569/IJARAI.2013.020301},
year = {2013},
publisher = {The Science and Information Organization},
volume = {2},
number = {3},
author = {Sheng-Fuu Lin and Jyun-Wei Chang}
}