UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 4 Issue 6
June-2017
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1706015


Registration ID:
170408

Page Number

67-69

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Title

Enhancing Electricity Theft Detection On User’s Metered Data

Abstract

The overall economic growth of India is mostly affected because of endemic electric energy and higher shortages of Electric power supply. Data mining has been used in numerous areas, which include both private as well as public sectors. This paper presents new ways to identify electricity theft by using some intelligence based techniques. The different techniques available for detecting electricity theft are Mobile Remote Checker, Wavelet based feature extraction, Support Vector Machine and Fuzzy based classification techniques. The most of the above mentioned methodologies have performance issues concerning space and time. This paper concentrates on analyzing techniques and to find a proper way to improve Electricity Theft Detection.

Key Words

Electricity theft, Expert system, Extreme Learning Machine (ELM), Online Sequential Extreme Learning Machine (OSELM), Intelligent system.

Cite This Article

"Enhancing Electricity Theft Detection On User’s Metered Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 6, page no.67-69, June-2017, Available :http://www.jetir.org/papers/JETIR1706015.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Enhancing Electricity Theft Detection On User’s Metered Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 6, page no. pp67-69, June-2017, Available at : http://www.jetir.org/papers/JETIR1706015.pdf

Publication Details

Published Paper ID: JETIR1706015
Registration ID: 170408
Published In: Volume 4 | Issue 6 | Year June-2017
DOI (Digital Object Identifier):
Page No: 67-69
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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