Enhancing the detection of fraudulent activities in the distribution of energy through data mining algorithms-Reference-Cited by-同舟云学术

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Enhancing the detection of fraudulent activities in the distribution of energy through data mining algorithms

Published:2023-05 Issue: Volume: Page:
ISSN:
Container-title:2023 24th International Conference on Control Systems and Computer Science (CSCS)
language:
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Author:

Gresoi Silviu¹,Mocanu Ştefan¹,Fǎgǎrǎşan Ioana¹,Stamatescu Grigore¹

Affiliation:

1. University Politehnica of Bucharest,Faculty of Automatic Control and Computers,Bucharest,Romania

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10214666/10214681/10214810.pdf?arnumber=10214810

Reference22 articles.

1. A hybrid data mining approach for anomaly detection and evaluation in residential buildings energy data

2. Data engineering for fraud detection

3. Detection of frauds and other non-technical losses in a power utility using Pearson coefficient, Bayesian networks and decision trees

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