GAs for fuzzy modeling of noise pollution

Caponetto, R and Lavorgna, M and Martinez, A and Occhipinti, L (1997) GAs for fuzzy modeling of noise pollution. In: UNSPECIFIED pp. 219-223..

Abstract

A growing problem in town areas is the noise pollution due to the increasing number of vehicles that daily cross the cities. A classical approach to model this kind of system is based on numeric regression, but its performances are not satisfactoring due to the non-linearity of the considered model. A suitable approach can be therefore to determine a fuzzy model of the system. There has been a considerable number of studies on fuzzy identification, where fuzzy implication are used to express rules, in this paper the Tagaki-Sugeno approach has been adopted applying a genetic algorithm during the optimization phase. The obtained model are compared with traditional one showing the suitability of the proposed method.