Water quality evaluation of surface water based on back propagation neural network

Xi-cheng, Xue; Yan, Chen

doi:10.1109/iswrep.2011.5893059

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Surface Water Excellence1

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2019

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“…In the proposed model the back propagation network was improved by means of select required number of configurations like number of hidden layers, nodes in the layers etc, in determining the surface water quality. Finally this work indicates that proposed back propagation model was ahead among traditional and back propagation water quality evaluation models [10].…”

Section: Surface Water Excellencementioning

confidence: 77%

Perspectives in Water Quality Assessment

2019

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One can assess the quality of water by water quality index method and it is a mathematical method to evaluate the water quality based on physical or chemical parameters, using WQI one can evaluate the water quality of both ground water and surface water, while determining the WQI one can use the standards or guidelines provided by some standard organizations like WHO (world health organization), National Standard Body of India (BIS), ICMR (Indian Council for Medical Research) etc. To assign grade to the water samples under study, apart from the WQI there are some other popular techniques used to evaluate water quality they are statistical methods, multivariate statistics, neural networks, fuzzy logic and machine learning algorithms. The aim of this study is to give insight into various methods used or developed to evaluate water quality of both ground and surface water by earlier research works.

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Section: Surface Water Excellencementioning

confidence: 77%

Perspectives in Water Quality Assessment

2019

ijrte

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Water quality evaluation of surface water based on back propagation neural network

Cited by 1 publication

References 0 publications

Perspectives in Water Quality Assessment

Perspectives in Water Quality Assessment

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