Complex Neuro Fuzzy System Using Complex Fuzzy Sets and Update the Parameters by PSO-GA and RLSE Method
P. Thirunavukarasu, R. Suresh, P. Thamilmani, South India · 2013
The novelty of the complex fuzzy sets lies in the range of values its membership function may attain. In contrast to a traditional fuzzy membership function, this range is not limited to (0, 1), but extended to the unit circle in the complex plane. Thus, the complex fuzzy set provides a mathematical framework for describing membership in a set in terms of a complex number. Based on the property of complex-valued membership, Complex fuzzy sets can be used to design a neural fuzzy system so that the Complex Neuro Fuzzy System (CNFS) can have excellent adaptive ability. The Hybrid PSO with GA is a multi-swarm-based optimization method, proposed by us, and it is used to adjust the premise parameters and the RLSE method is used to update the consequent parameters of the CNFS.