Intelligent feature engineered-machine learning based electricity theft detection framework for labelled and unlabelled datasets

Intelligent feature engineered-machine learning based electricity theft detection framework for labelled and unlabelled datasets

Non-Technical Losses (NTLs) in electrical utilities, primarily related to electrical theft, significantly impact energy supplier companies and the nation’s overall economy. Power distribution companies worldwide rely on time-consuming, laborious, and inefficient random onsite inspections to catch an...

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書目詳細資料
主要作者:	Hussain, Saddam
格式:	Thesis
語言:	English
出版:	2022
主題:	TK Electrical engineering Electronics Nuclear engineering
在線閱讀:	http://eprints.utm.my/id/eprint/102153/1/SaddamHussainPSKE2022.pdf.pdf
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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