Genetic-neuro-fuzzy systems: a promising fusion
Farley Simon Nobre · 2002
The aim of this paper is to emphasize some advantages of the fusion of artificial intelligence techniques such as fuzzy logic, neural nets and genetic algorithms. The design of neurofuzzy nets based on AND-OR logical neurons are discussed. Afterward, some ways for designing and automatic tuning of fuzzy system parameters using genetic algorithms are described. In the end, methods to provide parametric and structural learning of neural nets using genetic algorithms are presented and from these concepts the definition of regenerative neural nets is introduced.>