Estimation of Water Quality Index Talar River Using Gene Expression Programming and Artificial Neural Networks

Historically, rivers as a major source to supply drinking water and agriculture considered in human societies and very effective in the formation of civilizations. In addition, to this highly important place as valuable ecosystem. At present, most of north of rivers under the influence of human, that cause a variety of change and destruction of ecosystem. Pollution and human interfaces could be the most important factor to pollution caused by waste water of industrial, urban and rural, pollution resulting from disposal of pesticides used in agriculture ,destruction of vegetation construction of dam, and barriers under bridge, blocking the mouth of the river, illegal fishing. Hence, considering the importance of talar river for supply agriculture water, and also pour pollution to in, to identify and assess the river water quality and provide the necessary relationship to estimate pollution and water quality seems. In current study, used 72 samples during the years of 1391 to 1392 from 6 stations namely, weresk, pole sefid, shirgah, Talar,Kiakola and Arabkhil. Then, NSFWQI index was estimated. Then, with apply gene-expression programming and artificial neural network, obtained models for determination of relation between water quality parameters and water quality index with high accuracy. To evaluate the performance of models , statistical parameter such as, root mean square error, mean absolute error, scatter index and correlation coefficient were used. Results showed that the proper functioning of artificial neural networks and planning methods in estimating gene expression index is NSFWQI. The obtained results revealed appropriate performance of that artificial neural and gene-expression programming to estimate NSFWQI index.