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  Published Paper Details:

  Paper Title

WATER QUALITY PREDICTION USING MACHINE LEARNING ALGORITHMS

  Authors

  V QUEEN JEMILA,  M DHANALAKSHMI,  M AMUTHA

  Keywords

Water quality Index, Decision Tree, KNN, and Naive Bayes

  Abstract


The main task of our research work is to calculate the Water Quality Index of bore water in our surrounding educational institutions using three machine learning algorithms. Our research work differentiates from other work by choosing Decision Tree, K-Nearest Neighbor, and Naive Bayes Algorithms and their accuracy. We collected water samples from various resources and calculated the six important factors: salinity, total suspended solids (TDS), dissolved oxygen (DO), acidity and alkalinity (pH), and biochemical oxygen demand (BOD). The water quality parameters were analyzed using standard chemical methods. Using these parameters we created our own dataset and the dataset is given as our chosen algorithms train and test data. Finally, we got the WQI value with three different accuracies.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2312837

  Paper ID - 248724

  Page Number(s) - h442-h449

  Pubished in - Volume 11 | Issue 12 | December 2023

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.37442

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  V QUEEN JEMILA,  M DHANALAKSHMI,  M AMUTHA,   "WATER QUALITY PREDICTION USING MACHINE LEARNING ALGORITHMS", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 12, pp.h442-h449, December 2023, Available at :http://www.ijcrt.org/papers/IJCRT2312837.pdf

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ISSN: 2320-2882
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Journal Starting Year (ESTD) : 2013
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ISSN and 7.97 Impact Factor Details


ISSN
ISSN
ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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