Design of early warning model of electricity charge recovery risk based on clustering data cleaning
Pages 594 - 598
Abstract
In order to further improve the effect of electricity fee recovery risk early warning, this study designed a new electricity fee recovery risk early warning model based on clustering data cleaning. Based on the clustering data cleaning algorithm, formally clean the electricity fee recovery data, and use the DBSCAN algorithm to fill in the missing values in the data, and construct the electricity fee recovery risk warning index. Construct the electricity fee recovery risk warning model through the gray system model. The experimental results show that compared with the traditional early warning model, the risk prevention rate of this model is higher, and the early warning performance of the model is stronger.
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Index Terms
- Design of early warning model of electricity charge recovery risk based on clustering data cleaning
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Published In
November 2023
1156 pages
ISBN:9798400716478
DOI:10.1145/3656766
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 01 June 2024
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- Refereed limited
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ICBAR 2023
ICBAR 2023: 2023 3rd International Conference on Big Data, Artificial Intelligence and Risk Management
November 24 - 26, 2023
Chengdu, China
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