Forecasting Method of Electricity Charge based on Gray algorithm
Authors: 
Li Wu, Bei Yu, Xinrui Ju, Lihua JiangAuthors Info & Claims
Li Wu, Bei Yu, Xinrui Ju, Lihua JiangAuthors Info & ClaimsArticle No.: 96, Pages 1 - 7
Abstract
This paper focuses on the accuracy problem of medium and long-term enterprise electricity tariff prediction. Under the assumption that electricity users pay electricity charges on time, this paper takes into account the prediction problem of enterprise electricity sales. In this paper, the neighborhood rough set theory is used to extract the features of the influencing factors of power consumption. Based on the multivariate grey model GM (1, N), the independent variable sequence affecting the electricity prediction factor and the dependent variable sequence based on the electricity data of the industry are established, and the GM (1, N) model is modified by introducing linear correction coefficient and grey action. Combined with feature extraction, the results show that the improved GM (1, N) model has obvious improvement in operational efficiency and prediction accuracy.
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Published In
January 2021
1142 pages
ISBN:9781450389570
DOI:10.1145/3448734
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Published: 17 May 2021
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CONF-CDS 2021
CONF-CDS 2021: The 2nd International Conference on Computing and Data Science
January 28 - 30, 2021
CA, Stanford, USA
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