Title: Modelling nitrate pollution of groundwater using artificial neural network and genetic algorithm in an arid zone

Authors: Saeid Eslamian, Niloufar Lavaei

Addresses: Department of Water Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran. ' Department of Water Engineering, Isfahan University of Technology, Isfahan 84156-83111, Iran

Abstract: This paper presents a hybrid approach to analyse nitrate pollution based on an Artificial Neural Network (ANN) and Genetic Algorithm (GA). This makes it possible to compute the amount of nitrate in different time-scales easily without employment of confusing complicated mathematical equations. Generally, the results of the current research could be useful in management purposes and also for beneficiaries of groundwater. Isfahan province, located in a dry region of Iran, was chosen as the study area.

Keywords: nitrate pollution; water quality; groundwater pollution; water pollution; ANNs; artificial neural networks; GAs; genetic algorithms; dry land; arid zones; Iran.

DOI: 10.1504/IJW.2009.028726

International Journal of Water, 2009 Vol.5 No.2, pp.194 - 203

Available online: 25 Sep 2009 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article