Electricity Theft Detection using Machine Learning
نویسندگان
چکیده
This research work dealt with the indiscriminate theft of electric power, reported as a non-technical loss, affecting distribution companies and customers, triggering serious consequences including fires blackouts. The focused on recommending best prediction model using Machine Learning in electrical energy theft. source information electricity consumption 42372 consumers was dataset published State Grid Corporation China. method used data imputation, balancing (oversampling under sampling), feature extraction to improve detection. Five models were tested. As result, accuracy indicator SVM 81%, K-Nearest Neighbors 79%, Random Forest 80%, Logistic Regression 69%, Naive Bayes 68%. It is concluded that performance, an obtained by model.
منابع مشابه
Electricity Theft Detection using Machine Learning
Non-technical losses (NTL) in electric power grids arise through electricity theft, broken electric meters or billing errors. They can harm the power supplier as well as the whole economy of a country through losses of up to 40% of the total power distribution. For NTL detection, researchers use artificial intelligence to analyse data. This work is about improving the extraction of more meaning...
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Electricity load forecasting has become increasingly important due to the strong impact on the operational efficiency of the power system. However, the accurate load prediction remains a challenging task due to several issues such as the nonlinear character of the time series or the seasonal patterns it exhibits. A large variety of techniques have been proposed to this aim, such as statistical ...
متن کاملElectricity Load Forecasting Using Machine Learning Techniques
Electricity load forecasting has become increasingly important due to the strong impact on the operational efficiency of the power system. However, the accurate load prediction remains a challenging task due to several issues such as the nonlinear character of the time series or the seasonal patterns it exhibits. A large variety of techniques have been proposed to this aim, such as statistical ...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2022
ISSN: ['2158-107X', '2156-5570']
DOI: https://doi.org/10.14569/ijacsa.2022.0131251