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Research on Intelligent Prediction of Power Transformation Operation Cost Based on Multi-dimensional Mixed Information

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Advanced Hybrid Information Processing (ADHIP 2022)

Abstract

Operation cost is an important link in the operation of power enterprises. In the process of intelligent prediction of power transformation operation cost, there is a problem of low accuracy. Therefore, an intelligent prediction method of power transformation operation cost based on multi-dimensional mixed information is designed. Evaluate the fixed cost of power grid, determine the budget amount in different budget periods, extract the life cycle of power grid substation equipment, establish the cost estimation relationship, use multi-dimensional mixed information to build the cost control model, refine the project category, and optimize the intelligent prediction mode of operation cost according to the different nature of each link cost. Test results: the average prediction accuracy of the intelligent prediction method of power grid substation operation cost in this paper and the other two intelligent prediction methods of power grid substation operation cost are 79.357%, 71.066% and 69.313% respectively, indicating that after using multi-dimensional mixed information, the application effect of the designed intelligent prediction method of power grid substation operation cost is more prominent.

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Correspondence to Ying Wang .

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© 2023 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Wang, Y., Zhu, X., Ke, Y., Yu, J., Li, Y. (2023). Research on Intelligent Prediction of Power Transformation Operation Cost Based on Multi-dimensional Mixed Information. In: Fu, W., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 469. Springer, Cham. https://doi.org/10.1007/978-3-031-28867-8_5

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  • DOI: https://doi.org/10.1007/978-3-031-28867-8_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-28866-1

  • Online ISBN: 978-3-031-28867-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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