Prediction and estimation of atmospheric pollutant levels by soft computing approach

Author

Morabito, F.C. ; Versaci, M.

Author_Institution

Fac. of Eng., Univ. Mediterranea, Reggio Calabria, Italy

Volume

2

fYear

2001

fDate

2001

Firstpage

1415

Abstract

The goal of this paper is to design an environmental monitoring system which is able to estimate and predict the pollutant values of an important city area on the Strait of Messina (Italy). In order to solve the problem, we propose the use of neuro-fuzzy inference techniques. This approach utilizes the concepts of fuzzy inference systems (FIS) to estimate and predict the pollution level in the air. By using a specific MatLab^R Toolbox, we developed a sophisticated FIS. Each rule is of the IF...THEN structure in terms of linguistic framework in which the easy understanding due to the open box structure can help the politicians to take decisions about the urban traffic

Keywords

air pollution measurement; computerised monitoring; fuzzy neural nets; inference mechanisms; Strait of Messina; air pollution; atmospheric pollutant levels; environmental monitoring system; fuzzy inference systems; fuzzy neural networks; soft computing; urban traffic; Air pollution; Automatic control; Cities and towns; Computer languages; Control systems; Fuzzy systems; Lab-on-a-chip; Monitoring; Neural networks; Visual databases;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-7044-9

Type

conf

DOI

10.1109/IJCNN.2001.939569

Filename

939569