Impurity effect on clear water evaporation: toward modelling wastewater evaporation using ANN, ANFIS-SC and GEP techniques. Issue 11 (18th August 2017)

• Record Type: Journal Article
• Authors: Izady, A.; Sanikhani, H.; Abdalla, O.; Chen, M.; Kisi, O.
• Is Part Of: Hydrological sciences journal. Volume 62:Issue 11(2017)
• Page Start: 1856
• Page End: 1866
• Publication Date: 2017-08-18
• Subjects: wastewater -- evaporation -- neural networks -- subtractive clustering -- gene expression programming; Hydrology -- Periodicals; 551.4805
• DOI: 10.1080/02626667.2017.1356023
• Languages: English
• ISSNs: 0262-6667

Abstract

ABSTRACT: The growing shortage of freshwater resources and increasing environmental awareness give rise to the use of treated wastewater as an alternative resource for water supply. Accurate estimation of wastewater evaporation (WWE), as the main cause of water losses, is necessary for proper water resources management. Unfortunately, few studies have focused on modelling WWE despite its vital importance. This study investigates the ability of gene expression programming (GEP), adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANN) techniques to estimate WWE as a function of variables including wastewater properties, clear water evaporation and climatic factors. The study uses measured data from an experiment conducted in Neishaboor municipal wastewater treatment plant, Iran. Results indicate that the ANN model is superior among the three methods, and also demonstrates higher accuracy when compared with those of a dimensional analysis model using the F-test statistic.