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Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach

Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable locat...

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Autores principales: Shimray, Benjamin A., Singh, Kh. Manglem, Khelchandra, Thongam, Mehta, R. K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346385/
https://www.ncbi.nlm.nih.gov/pubmed/28331490
http://dx.doi.org/10.1155/2017/4152140
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author Shimray, Benjamin A.
Singh, Kh. Manglem
Khelchandra, Thongam
Mehta, R. K.
author_facet Shimray, Benjamin A.
Singh, Kh. Manglem
Khelchandra, Thongam
Mehta, R. K.
author_sort Shimray, Benjamin A.
collection PubMed
description Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant installation site is an issue of relevance. Environmental impact assessment is often used as a legislative requirement in site selection for decades. The purpose of this current work is to develop a model for decision makers to rank or classify various power plant projects according to multiple criteria attributes such as air quality, water quality, cost of energy delivery, ecological impact, natural hazard, and project duration. The case study in the paper relates to the application of multilayer perceptron trained by genetic algorithm for ranking various power plant locations in India.
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spelling pubmed-53463852017-03-22 Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach Shimray, Benjamin A. Singh, Kh. Manglem Khelchandra, Thongam Mehta, R. K. Comput Intell Neurosci Research Article Every energy system which we consider is an entity by itself, defined by parameters which are interrelated according to some physical laws. In recent year tremendous importance is given in research on site selection in an imprecise environment. In this context, decision making for the suitable location of power plant installation site is an issue of relevance. Environmental impact assessment is often used as a legislative requirement in site selection for decades. The purpose of this current work is to develop a model for decision makers to rank or classify various power plant projects according to multiple criteria attributes such as air quality, water quality, cost of energy delivery, ecological impact, natural hazard, and project duration. The case study in the paper relates to the application of multilayer perceptron trained by genetic algorithm for ranking various power plant locations in India. Hindawi Publishing Corporation 2017 2017-02-26 /pmc/articles/PMC5346385/ /pubmed/28331490 http://dx.doi.org/10.1155/2017/4152140 Text en Copyright © 2017 Benjamin A. Shimray et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Shimray, Benjamin A.
Singh, Kh. Manglem
Khelchandra, Thongam
Mehta, R. K.
Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach
title Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach
title_full Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach
title_fullStr Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach
title_full_unstemmed Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach
title_short Ranking of Sites for Installation of Hydropower Plant Using MLP Neural Network Trained with GA: A MADM Approach
title_sort ranking of sites for installation of hydropower plant using mlp neural network trained with ga: a madm approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5346385/
https://www.ncbi.nlm.nih.gov/pubmed/28331490
http://dx.doi.org/10.1155/2017/4152140
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