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  Published Paper Details:

  Paper Title

AN APPROACH FOR DETECTION AND PREVENTION OF ELECTRICITY PILFERAGE USING MACHINE LEARNING

  Authors

  Satish S. Banait,  Darshana S. Sarode,  Kapil M. Shelke,  Himesh S. Rathod,  Akash V. Galande

  Keywords

non technical loss, electricity theft, pipeline, imbalanced dataset, machine learning.

  Abstract


Electricity theft is the primary cause of electricity power loss that significantly affects the revenue loss and the quality of electricity power. Nevertheless, the existing methods for the detection of this criminal behaviour of theft are diversified and dimensionality of time-series data makes it challenging to extract meaningful information. This paper addresses these problems by developing a novel electricity theft detection model, integrating three algorithms. The proposed method first applies the synthetic minority oversampling technique for balancing the dataset, secondly we apply pre-processing on smart meter data then do feature selection. Extensive experiments are performed by using real electricity consumption data, and results show that the proposed method outperforms other methods in terms of theft detection.

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2303243

  Paper ID - 232373

  Page Number(s) - c236-c239

  Pubished in - Volume 11 | Issue 3 | March 2023

  DOI (Digital Object Identifier) -   

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

  E-ISSN Number - 2320-2882

  Cite this article

  Satish S. Banait,  Darshana S. Sarode,  Kapil M. Shelke,  Himesh S. Rathod,  Akash V. Galande,   "AN APPROACH FOR DETECTION AND PREVENTION OF ELECTRICITY PILFERAGE USING MACHINE LEARNING", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.11, Issue 3, pp.c236-c239, March 2023, Available at :http://www.ijcrt.org/papers/IJCRT2303243.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


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