PERFORMANCE EFFICIENCY ANALYSIS OF WATER TREATMENT PLANTS BY USING MCDM AND NEURAL NETWORK MODEL

Authors

  • Apu Kumar Saha Department of Mathematics, National Institute of Technology, Agartala, Tripura, India
  • Sudipa Choudhury Department of Mathematics, National Institute of Technology, Agartala, Tripura, India
  • Mrinmoy Majumder School of Hydro-Informatics Engineering (Under Civil Engineering Department), National Institute of Technology, Agartala, Tripura, India

DOI:

https://doi.org/10.20319/Mijst.2017.31.2735

Keywords:

Water Treatment Plant, MCDM, NSFDSS, ANN

Abstract

The organization of safe and sustainable sources of water remains a priority for decision makers around the world. The centrality of water in public health as well as in industry creates a high demand for water supply of suitable quality that many nations around the world are harassed to meet. In India, in particular, water shortages and poor water quality continue to be major challenges in both domestic and industrial sectors. That is why, the evaluation of the performance efficiency of the existing water treatment plant is essential. This paper utilizes the Non-structural Fuzzy Decision Support System (NSFDSS) as well as Artificial Neural Network (ANN) to identify the parameter that is most significant in helping the decision makers to build an efficient water treatment plant operating system.

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Published

2017-03-15

How to Cite

Saha, A. K., Choudhury, S., & Majumder, M. (2017). PERFORMANCE EFFICIENCY ANALYSIS OF WATER TREATMENT PLANTS BY USING MCDM AND NEURAL NETWORK MODEL. MATTER: International Journal of Science and Technology, 3(1), 27–35. https://doi.org/10.20319/Mijst.2017.31.2735

Issue

Vol. 3 No. 1 (2017): Regular Issue

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Articles

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