Big Data Cleaning Based on Improved CLOF and Random Forest for Distribution Networks

Big Data Cleaning Based on Improved CLOF and Random Forest for Distribution Networks

In order to improve the data quality, the big data cleaning method for distribution networks is studied in this paper. First, the Local Outlier Factor (LOF) algorithm based on DBSCAN clustering is used to detect outliers. However, due to the difficulty in determining the LOF threshold, a method of d...

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Bibliographic Details
Main Authors: Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng
Format: Article
Language:English
Published: China electric power research institute 2024-01-01
Series:CSEE Journal of Power and Energy Systems
Subjects:
Data cleaning
DBSCAN
LOF
missing data imputation
outliers detection
Random Forest
Online Access:https://ieeexplore.ieee.org/document/9299499/
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