Model Construction of Power Company Investment Capacity Based on Artificial Intelligence Technology

Shaodong Luo, Youhua Li, Ji Zhan and Yuanyuan Cao

Chapter 72 in Internet Finance and Digital Economy:Advances in Digital Economy and Data Analysis Technology, 2023, pp 953-963 from World Scientific Publishing Co. Pte. Ltd.

Abstract: With the continuous development of the national economy, the social demand for electricity continues to increase, and the scale of investment in the power grid is also increasing. However, in recent years, the growth rate of electricity sales has slowed down due to the influence of national macro-control and industrial structure adjustment. In order to solve the problems faced by power companies in power investment management, this paper uses artificial intelligence technology to build a power company’s investment capability model. After summarizing the factors that affect the company’s investment, the calculation method of the relevant investment capacity of the power company is put forward. Through the application of the investment capacity model of the power company, it is estimated that the fixed assets will increase by 31.5 billion yuan, 31.1 billion yuan, and 32.4 billion yuan, respectively, in the next three years., totaling 95 billion yuan. After deducting inventory depreciation and new assets, the investment in the next three years will affect the company’s net increase in fixed assets of 11.7 billion yuan, 9.2 billion yuan, and 8.2 billion yuan, totaling 29.1 billion yuan, the audited investment scale in the next three years will be 41.7 billion yuan, 41.3 billion yuan, and 43 billion yuan respectively, totaling 1,260 yuan. The construction and application of this model are beneficial for power enterprises to optimize the allocation of limited resources and achieve precise and lean investment management.

Keywords: Internet Economy; Online Finance; Financial Engineering; Big Data; Blockchain; Supply Chain; E-commerce (search for similar items in EconPapers)
JEL-codes: G2 O33 (search for similar items in EconPapers)
Date: 2023
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