Environmental Modeling by means of Genetic Fuzzy Systems

Abstract

In this work four genetic fuzzy system are applied to an environmental problem, i.e. modeling ozone concentrations in Mexico City metropolitan area. These hybrid systems are composed by the Fuzzy Inductive Reasoning (FIR) methodology and different genetic algorithms (GAs) that takes charge of determining, in an automatic way, the fuzzification parameters. Mexico is the second country in the world with high air pollution levels. The main air pollution problem that has been identified in Mexico City metropolitan area is the formation of photochemical smog, primarily ozone. This toxic gas can produce harmful effects on the population's health. The study and development of modeling methodologies that allow the capturing of ozone behavior becomes an important task when it is intended to predict contingencies before they are produced.