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  Published Paper Details:

  Paper Title

Data Mining and Artificial Intelligence in Water Supply Management System

  Authors

  Nayana S Jirankali,  Shreyus Yadaveerappa Kouty

  Keywords

Data Mining, Data Warehouse, Water Supply Management, Artificial Intelligence

  Abstract


This paper discusses about the data driven intelligence role in managing the water resources, pipelines, infrastructures, geographical and environmental conditions required for the urban water supply using information technology like Data Mining. Implementation and maintenance of the uninterrupted water supply system using Artificial Intelligence with the help of building the Data Warehouse. Focus on use cases related to solutions for the challenges in water supply management in the urban areas due to fast growing and dynamically changing inhabitation to meet the required quantity without compromise in quality considering cost indices. Optimizing the productivity and strengthening the information management is the main driving force to improve the ability to sustain the requirement, this can be achieved using GIS in Data Mining to gather the information, Data Warehouse technologies to store the data in organized way, implementation and maintenance using Artificial Intelligence technology.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2307568

  Paper ID - 241514

  Page Number(s) - e900-e908

  Pubished in - Volume 11 | Issue 7 | July 2023

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Nayana S Jirankali,  Shreyus Yadaveerappa Kouty,   "Data Mining and Artificial Intelligence in Water Supply Management System", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 7, pp.e900-e908, July 2023, Available at :http://www.ijcrt.org/papers/IJCRT2307568.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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