Application of artificial intelligence (AI) techniques in water quality index prediction: a case study in tropical region, Malaysia

Mohammed Hameed, Saadi Shartooh Sharqi, Zaher Mundher Yaseen, Haitham Abdulmohsin Afan, Aini Hussain, Ahmed Elshafie

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

The management of river water quality is one the most significant environmental challenges. Water quality index (WQI) describes several water quality variables at a certain aquatic environment and time. Classically, WQI is commonly computed using the traditional methods which involved lengthy computation, consume timing and occasionally associated with accidental errors during subindex calculation. Thus, providing an accurate prediction model for WQI is highly required. Recently, the artificial neural networks (ANNs) have been examined for similar prediction applications and exhibited a remarkable ability to capture the nonlinearity pattern between predictors and predictand. In the current research, two different ANN algorithms, namely radial basis function neural network (RBFNN) and back propagation neural networks models, have been applied to examine and mimic the relationship of WQI with the water quality variables in a tropical environment (Malaysia). The input variables categorized into two different architectures and have been inspected. In addition, comprehensive analysis for the performance evaluation and the sensitivity analysis of the variables have been conducted. The results achieved are positively promising with high performance accuracy belonging to RBFNN model for both scenarios. Furthermore, the proposed approach offers an effective alternative to compute and predict WQI, to the fact that WQI manual calculation methods involved lengthy computations, transformations, use of various subindex formulae for each value of the constituent water quality variables, and consuming time.

Original languageEnglish
Pages (from-to)1-13
Number of pages13
JournalNeural Computing and Applications
DOIs
Publication statusAccepted/In press - 8 Jun 2016

Fingerprint

Water quality
Artificial intelligence
Neural networks
Backpropagation
Sensitivity analysis
Rivers

Keywords

  • Artificial neural networks
  • BPNN
  • RBFNN
  • Tropical environment
  • Water quality index
  • Water quality variables

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Application of artificial intelligence (AI) techniques in water quality index prediction : a case study in tropical region, Malaysia. / Hameed, Mohammed; Sharqi, Saadi Shartooh; Yaseen, Zaher Mundher; Afan, Haitham Abdulmohsin; Hussain, Aini; Elshafie, Ahmed.

In: Neural Computing and Applications, 08.06.2016, p. 1-13.

Research output: Contribution to journalArticle

Hameed, Mohammed ; Sharqi, Saadi Shartooh ; Yaseen, Zaher Mundher ; Afan, Haitham Abdulmohsin ; Hussain, Aini ; Elshafie, Ahmed. / Application of artificial intelligence (AI) techniques in water quality index prediction : a case study in tropical region, Malaysia. In: Neural Computing and Applications. 2016 ; pp. 1-13.
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