Impurity effect on clear water evaporation: toward modelling wastewater evaporation using ANN, ANFIS-SC and GEP techniques: toward modelling wastewater evaporation using ANN, ANFIS-SC and GEP techniques

A. Izady*, H. Sanikhani, O. Abdalla, M. Chen, O. Kisi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1856-1866
Number of pages11
JournalHydrological Sciences Journal
Volume62
Issue number11
DOIs
Publication statusPublished - Aug 18 2017
Externally publishedYes

Keywords

  • evaporation
  • gene expression programming
  • neural networks
  • subtractive clustering
  • wastewater

ASJC Scopus subject areas

  • Water Science and Technology

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