MultiGrid-Based Fuzzy Systems for Function Approximation

In this paper we make use of a modified Grid Based Fuzzy System architecture, which may provide an exponential reduction in the number of rules needed. We also introduce an algorithm that automatically, from a set of given I/O training points, is able to determine the pseudo-optimal architecture proposed as well as the optimal parameters needed (number and position of membership functions and fuzzy rule consequents). The suitability of the algorithm and the improvement in both performance and efficiency obtained are shown in an example.

• Type: Conference
• Year: 2004
• Where: MICAI
• Authors: Luis Javier Herrera, Héctor Pomares, Ignacio Rojas, Olga Valenzuela, Mohammed Awad
• Keywords: Artificial Intelligence, Fuzzy Rule Consequents, Fuzzy System Architecture, I/O Training Points, MICAI 2004