BibTeX:

@article{IJIRSTV1I9023,
     title={Detection of Non-Technical Loss in Power Utilities Using Data Mining Techniques},
     author={Rajesh. R, E.Siva Sankari and P.Matheswaran},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={1},
     number={9},
     pages={97--101},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV1I9023.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

This paper presents Non-Technical loss (NTL) in power utilities and it describes how to handle. Non-technical loss has been an influential factor on the benefits of electric power utilities. At the same time, with distribute generation extensively installed, the consumption patterns having many similarities between dishonest users and normal customers. Non-Technical Loss may be theft of electricity, illegal connection, fault metering and billing error. Improving the reliability of NTL detection algorithm becomes particularly important. Data mining techniques are used to detect the Non-Technical Loss using classification algorithm. The implementation of a intelligent computational tool to identify the non-technical losses and to select its most close feature, considering information from the database with consumers profiles. This work presents using the weka software to the proposed objective, comparing various classification techniques and optimization through intelligent algorithm.

Multilayer Perceptron, Data Mining, Non-Technical Loss