Transformation of a Mamdani FIS to First Order Sugeno FIS

— In many decision support applications it is important to guarantee the expressive power, easy formalization and interpretability of Mamdani-type fuzzy inference systems (FIS), while ensuring the computational efficiency and accuracy of Sugeno-type FIS. Hence, in this paper we present an approach to transform a Mamdani-type FIS into a Sugeno-type FIS. We consider the problem of mapping Mamdani FIS to Sugeno FIS as an optimization problem and by determining the first order Sugeno parameters, the transformation is achieved. To solve this optimization problem we compare three methods: Least Squares, Genetic Algorithms and an adaptive neuro-fuzzy inference system. An illustrative example is presented to discuss the approaches.

• Type: Conference
• Year: 2007
• Where: FUZZIEEE
• Authors: Javad Jassbi, S. H. Alavi, Paulo J. A. Serra, Rita Almeida Ribeiro
• Keywords: FUZZIEEE 2007, Fuzzy Logic, Inference System, Optimization Problem, Sugeno-type FIS