Interval type-2 fuzzy expert system for prediction of carbon monoxide concentration in mega-cities

Authors:
M.H. Fazel Zarandi;M. R. Faraji;M. Karbasian
Affiliations:
Department of Industrial Engineering, Amirkabir University of Technology (Polytechnic of Tehran), P.O. Box 15875-4413, Tehran, Iran;Department of Industrial Engineering, Amirkabir University of Technology (Polytechnic of Tehran), P.O. Box 15875-4413, Tehran, Iran;Department of Industrial Engineering, Amirkabir University of Technology (Polytechnic of Tehran), P.O. Box 15875-4413, Tehran, Iran
Venue:
Applied Soft Computing
Year:
2012

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Abstract

This paper presents an indirect approach to interval type-2 fuzzy logic system modeling to forecaste the level of air pollutants. The type-2 fuzzy logic system permits us to model the uncertainties among rules and the parameters related to data analysis. In this paper, we propose an indirect method to create an interval type-2 fuzzy logic system from a historical data, where Footprint of Uncertainties of fuzzy sets are extracted by implementation of an interval type-2 FCM algorithm and based on an upper and lower value for the level of fuzziness m in FCM. Finally, the proposed model is applied for prediction of carbon monoxide concentration in Tehran air pollution. It is shown that the proposed type-2 fuzzy logic system is superior in comparison to type-1 fuzzy logic systems in terms of two performance indices.