Neural networks and genetic algorithm approaches to auto-design of fuzzy systems

1 Introduction / 2 Neural Network Approaches / 3 Genetic Algorithm Approaches / 4 ConclusionThis paper presents Neural Network and Genetic Algorithm approaches to fuzzy system design, which aims to shorten development time and increase system performance. An approach that uses neural network to represent multi-dimensional nonlinear membership functions and an approach to tune membership function parameters are given. A genetic algorithm approach that integrates and automates three fuzzy system design stages is also proposed