The prediction of air pollution by using Neuro-fuzzy GMDH

Air pollution is one of today modern life phenomena. It is resulted to create round-the-clock human begin activities. Control of environment pollution is complicated scientific process that enters policy, economy, technology and sociology. GMDH (Group Method of Data Handling) has been used for the identification of a mathematical model that has many input variables but limited data needs by using a hierarchical structure. This paper proposes a Neuro-fuzzy GMDH model, adopting Gaussian radial basis functions (GRBF) as partial descriptions of GMDH. GRBF is reinterpreted as both a simplified fuzzy reasoning model and as a three-layered neural network. In this paper, is used Neuro-fuzzy GMDH algorithm for predicting air pollution data and then were compared the results of predicting air pollution data by using Neuro-fuzzy GMDH and Multi Layer Perceptron (MLP).