The Application of Big Data in Cost Control and Budgeting of Power Financial Management

DOI

10.2991/978-94-6239-602-9_5How to use a DOI?

Keywords

big data; Financial management of electricity; Cost control; Budget; Bayesian network; Financial Decision Model

Abstract

This article explores the application of big data in cost control and budgeting in power financial management. Firstly, it elaborates on the role of big data technology in financial management of power enterprises, and points out the need to build a financial center database with multiple modules to mine and integrate data through cloud computing to improve management efficiency; Next, explain the process of constructing a financial decision-making model for enterprises, including data preprocessing, Bayesian network structure learning based on K2 algorithm, parameter learning, and post correction mechanism; Finally, a comparative experiment was conducted using a certain power enterprise as a case study, and the results showed that the financial decision support model based on post modified Bayesian networks can more effectively reduce enterprise costs, improve profits, optimize asset liability ratios, and provide scientific support for financial cost control and budgeting in power enterprises compared to the other two methods.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Jinxiu Zhang
AU  - Zhipeng Li
AU  - Shuo Shen
AU  - Yixuan Chen
AU  - Jun Wang
PY  - 2026
DA  - 2026/03/13
TI  - The Application of Big Data in Cost Control and Budgeting of Power Financial Management
BT  - Proceedings of the 2025 7th International Conference on Economic Management and Model Engineering (ICEMME 2025)
PB  - Atlantis Press
SP  - 39
EP  - 47
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6239-602-9_5
DO  - 10.2991/978-94-6239-602-9_5
ID  - Zhang2026
ER  -