Open AccessPredicting the process of industrial wastewater treatment using a hybrid intelligent model based on artificial neural network and logistic regression statistical method
Author(s) -
Mirheydar Garsi Effat,
Ahmad Jafarian
Publication year - 2016
Publication title -
bulletin de la société royale des sciences de liège
Language(s) - English
Resource type - Journals
ISSN - 1783-5720
DOI - 10.25518/0037-9565.5363
Subject(s) - artificial neural network , malachite green , logistic regression , process (computing) , computer science , artificial intelligence , machine learning , data mining , engineering , operating system , chemistry , organic chemistry , adsorption
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.