Modeling and Identification of complex systems using Neuro-Fuzzy Techniques.(Dept.E)

In this paper Adaptive-Network-Based Fuzzy Inference System (ANFIS) architecture is presented and has been used as a tool for System Identification. System Identification consists of three related steps: 1:) Structure specification, 2:) Parameter estimation. 3:) Model Validation. These steps are also discussed. We use a new method to determine the structure of the ANFIS model (Fuzzy Curves). Fuzzy Curves Help in determining the number of significant inputs from a number of candidates. We determine the number of membership functions in each input by using the subtractive clustering. Finally this method is tested on two cases.