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JCR 2016
جستجوی مقالات
دوشنبه 1 دی 1404
Journal of Advances in Environmental Health Research
، جلد ۱، شماره ۲، صفحات ۸۹-۰
عنوان فارسی
چکیده فارسی مقاله
کلیدواژههای فارسی مقاله
عنوان انگلیسی
Application of artificial neural network (ANN) for the prediction of water treatment plant influent characteristics
چکیده انگلیسی مقاله
Application of a reliable forecasting model for any water treatment plant (WTP) is essential in order to provide a tool for predicting influent water quality and to form a basis for controlling the operation of the process. This would minimize the operation and analysis costs, and assess the stability of WTP performances. This paper focuses on applying an artificial neural network (ANN) approach with a feed-forward back-propagation non-linear autoregressive neural network to predict the influent water quality of Sanandaj WTP. Influent water quality data gathered over a 2-year period were used to building the prediction model. The study signifies that the ANN can predict the influent water quality parameters with a correlation coefficient (R) between the observed and predicted output variables reaching up to 0.93. The prediction models developed in this work for Alkalinity, pH, calcium, carbon dioxide, temperature, total hardness, turbidity, total dissolved solids, and electrical conductivity have an acceptable generalization capability and accuracy with coefficient of determination (R 2 ) ranging from 0.86 for alkalinity to 0.54 for electrical conductivity. The predicting ANN model provides an effective analyzing and diagnosing tool to understand and simulate the non-linear behavior of the influent water characteristics. The developed predicting models can be used by WTP operators and decision makers.
کلیدواژههای انگلیسی مقاله
نویسندگان مقاله
مهری سلیمانی aminabad | mehri solaimany aminabad
kurdistan environmental health research center, school of health, kurdistan university of medical sciences, sanandaj, iran
افشین ملکی | afshin maleki
kurdistan environmental health research center, school of health, kurdistan university of medical sciences, sanandaj, iran
مهدی هادی | mahdi hadi
center for water quality research cwqr , institute for environmental research ier , tehran university of medical sciences, tehran, iran
سازمان اصلی تایید شده
: دانشگاه علوم پزشکی تهران (Tehran university of medical sciences)
نشانی اینترنتی
http://jaehr.muk.ac.ir/index.php/jaehr/article/view/47
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زبان مقاله منتشر شده
en
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