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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2017
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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. |
format | Online Article Text |
id | pubmed-5346385 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
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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