Research on power failure classification and identification of low-voltage users in low-voltage distribution network based on Internet of Things technology

Wei Yu; Yifang Su; Yuanhong Liu; Yan Tao; Wei Liu; Mingxin Zhao; Jinyu Wang

doi:10.1117/12.2671674

1 June 2023 Research on power failure classification and identification of low-voltage users in low-voltage distribution network based on Internet of Things technology

Wei Yu, Yifang Su, Yuanhong Liu, Yan Tao, Wei Liu, Mingxin Zhao, Jinyu Wang

Author Affiliations +

Proceedings Volume 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022); 126252U (2023) https://doi.org/10.1117/12.2671674
Event: International Conference on Mathematics, Modeling and Computer Science (MMCS2022),, 2022, Wuhan, China

Abstract

In China's social and economic development, stable development and suppression of fluctuation are the basic goals of macroeconomic policy. Due to the cyclical characteristics of China's financial and economic development, the construction of cyclical early warning mechanism in practical exploration can not only accurately predict the development trend of financial economy, but also help government departments and market institutions to make effective decisions. This paper is understanding China's financial and economic development trend and risk cycle early warning mechanism. Based on the research situation, the early warning mechanism with BP algorithm is deeply discussed. The final experimental results prove that we should continue to strengthen the research on the early warning mechanism of neural network in the financial and economic cycle.

Citation Download Citation

Wei Yu, Yifang Su, Yuanhong Liu, Yan Tao, Wei Liu, Mingxin Zhao, and Jinyu Wang "Research on power failure classification and identification of low-voltage users in low-voltage distribution network based on Internet of Things technology", Proc. SPIE 12625, International Conference on Mathematics, Modeling, and Computer Science (MMCS2022), 126252U (1 June 2023); https://doi.org/10.1117/12.2671674

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