Bulletin de la Société Royale des Sciences de Liège

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Mirheydar Garsi Effat & Jafarian Ahmad

Predicting the process of industrial wastewater treatment using a hybrid intelligent model based on artificial neural network and logistic regression statistical method

(Volume 85 - Année 2016 — Actes de colloques — Special edition)
DOI: 10.25518/0037-9565.5363
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Open Access

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Abstract

Today, there are different methods for treatment of wastewaters but due to their high cost and time-consuming features, an alternative precise, low cost; short-time method is always needed. Therefore, in this paper, we tried to employ a hybrid intelligent model based on artificial neural network (ANN) and logistic regression (LR) statistical method for wastewater treatment to predict the performance of malachite green removal from industrial wastewaters. Through comparing the prediction results and analyzed data, it proved that using a hybrid intelligent model based on artificial neural network and logistic regression statistical method is a valuable technique to predict the performance of malachite green removal from industrial wastewaters with high efficiency and minimum error rate.

Keywords : artificial neural network, green malachite, hybrid intelligent model, industrial wastewater, logistic regression

Para citar este artículo

Mirheydar Garsi Effat & Jafarian Ahmad, «Predicting the process of industrial wastewater treatment using a hybrid intelligent model based on artificial neural network and logistic regression statistical method», Bulletin de la Société Royale des Sciences de Liège [En ligne], Volume 85 - Année 2016, Actes de colloques, Special edition, 304 - 320 URL : http://popups.ulg.be/0037-9565/index.php?id=5363.

Acerca de: Mirheydar Garsi Effat

Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, Iran, jafarian5594@yahoo.com

Acerca de: Jafarian Ahmad

Department of Mathematics, Urmia Branch, Islamic Azad University, Urmia, Iran