Development of fuzzy regression models using genetic algorithms

Authors:
A. V. Mogilenko;D. A. Pavlyuchenko;V. Z. Manusov
Affiliations:
Department of Power Engineering, Novosibirsk State Technical University, 20, Karl Marx prospect, Novosibirsk, 630092, Russia;Department of Power Engineering, Novosibirsk State Technical University, 20, Karl Marx prospect, Novosibirsk, 630092, Russia;Department of Power Engineering, Novosibirsk State Technical University, 20, Karl Marx prospect, Novosibirsk, 630092, Russia
Venue:
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Year:
2003

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Abstract

This paper presents the comparative study for fuzzy regression model using linear programming and fuzzy regression model using genetic algorithms. Two cases were considered: crisp X - crisp Y and crisp X - fuzzy Y. Simulation was carried out with a tool developed in MATLAB.