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Construction of Intelligent Evaluation Model for Electric Power Marketing Inspection Status Based on Cloud Measurement

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Multimedia Technology and Enhanced Learning (ICMTEL 2023)

Abstract

The reform of electricity market and the acceleration of the construction of smart grid impel electric power enterprises to change the traditional marketing mode, realize the low loss conversion between complex information, and reduce the loss in the process of information cognition. An intelligent evaluation model of electric power marketing inspection status based on cloud measurement is proposed. Based on the overview of cloud measure, this paper analyzes the audit risk of electric power marketing, determines the index weight of electric power marketing audit state by constructing the evaluation index system of electric power marketing audit state, and realizes the intelligent evaluation of electric power marketing audit state by constructing the early warning model of electric power marketing audit state. The results of the example show that the model in this paper has certain feasibility and practicability in evaluating the electric power marketing inspection status. Through the cloud measurement analysis based on the cloud center of gravity, the objective expression of the electric power marketing status evaluation and early warning conclusion is obtained, which provides a new idea for the electric power marketing management decision-making.

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Correspondence to Yanli Zhang .

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© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zhang, Y., Zhang, X., Wang, L., Niu, R., Guo, W., Zhang, C. (2024). Construction of Intelligent Evaluation Model for Electric Power Marketing Inspection Status Based on Cloud Measurement. In: Wang, B., Hu, Z., Jiang, X., Zhang, YD. (eds) Multimedia Technology and Enhanced Learning. ICMTEL 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 532. Springer, Cham. https://doi.org/10.1007/978-3-031-50571-3_35

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  • DOI: https://doi.org/10.1007/978-3-031-50571-3_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50570-6

  • Online ISBN: 978-3-031-50571-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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