Comparison of Mamdani and Sugeno Fuzzy Inference Systems for Prediction (With Application to Prices of Fund in Egypt)
Hegazy Zaher
Department of Mathematical Statistics, Institute of Statistical Studies and Research (ISSR), Cairo University, Egypt.
Abd Elfattah Kandil
Department of Statistics and Mathematics, Benha University, Egypt.
Raafat Fahmy *
Department of Statistics and Mathematics, Benha University, Egypt.
*Author to whom correspondence should be addressed.
Abstract
This paper outlines the basic difference between the Mamdani/Sugeno Fuzzy inference systems (FIS) and the actual values. The main motivation behind this research is to assess which approach provides the best performance for predicting prices of Fund.
Due to the importance of performance in Economy, the Mamdani and Sugeno models are compared using four types of membership function (MF) generation methods: the Triangular, Trapezoidal, Gaussian and Gbell.
Fuzzy inference systems (Mamdani and Sugeno fuzzy models) can be used to predict the weekly prices of Fund for the Egyptian Market. The application results indicate that Sugeno model is better than that of Mamdani. The results of the two fuzzy inference systems (FIS) are compared.
Keywords: Fuzzy Inference System (FIS), fuzzy logic, Mamdani FIS, Sugeno FIS, prices of fund.