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Published in:

Volume 8 Issue 3
March-2021
eISSN: 2349-5162

Unique Identifier

JETIR2103044

Page Number

284-289

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Title

A STUDY ON MACHINE LEARNING APPROACHES FOR WATER QUALITY DETECTION

ISSN

2349-5162

Cite This Article

"A STUDY ON MACHINE LEARNING APPROACHES FOR WATER QUALITY DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 3, page no.284-289, March-2021, Available :http://www.jetir.org/papers/JETIR2103044.pdf

Abstract

Water is an inorganic , transparent , tasteless , odourless chemical substance , which is the one of the main constituents of the Earth’s hydrosphere and is significant for all vital forms of life but Rapid urbanization has result in its deterioration . Predicting recreational water quality in inexpensive ways is one in every of the foremost difficult task and so as to try to do that the models and algorithms of machine learning were explored by the researchers . The model includes artificial (ANN) , deep (DNN) , recurrent neural network (RNN) , linear discriminant analysis (LDA) , super vector machines (SVM), logistic regression and long-short term memory (LSTM) while the algorithms checks the water quality index (WQI) and also the water quality class (WQC) . The Simulation study is conducted to test performance of every algorithm using F-score metric . The study was conducted so as to analyse the algorithms and methods together and can further provide the sunshine to the trail of future research on the water quality detection using advanced techniques .

Key Words

Machine Learning , Water Quality , Water Quality Index

Cite This Article

"A STUDY ON MACHINE LEARNING APPROACHES FOR WATER QUALITY DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp284-289, March-2021, Available at : http://www.jetir.org/papers/JETIR2103044.pdf

Publication Details

Published Paper ID: JETIR2103044
Registration ID: 306379
Published In: Volume 8 | Issue 3 | Year March-2021
DOI (Digital Object Identifier):
Page No: 284-289
ISSN Number: 2349-5162

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Cite This Article

"A STUDY ON MACHINE LEARNING APPROACHES FOR WATER QUALITY DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp284-289, March-2021, Available at : http://www.jetir.org/papers/JETIR2103044.pdf




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