Research on the Price Prediction Technology of Power Grid Transformer Equipment Based on Least Squares-Multiple Linear Regression Model

DOI

10.2991/978-94-6463-736-6_28How to use a DOI?

Keywords

transformer; least squares; multiple linear regression; price prediction

Abstract

This study addresses the challenges in predicting transformer equipment prices during the feasibility and design phases of power grid projects. By integrating historical data with a least-squares-based multiple linear regression model, this approach enhances prediction precision, enabling more effective pre-construction budgeting and dynamic cost management. The proposed methodology is designed to adapt to market fluctuations, offering robust guidance for cost control and investment planning in grid engineering.

Copyright

© 2025 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  - Yan Li
AU  - Yabo Shen
AU  - Gaosheng Rong
AU  - Suriya Dirisatii
AU  - Xuehua Zhao
PY  - 2025
DA  - 2025/05/22
TI  - Research on the Price Prediction Technology of Power Grid Transformer Equipment Based on Least Squares-Multiple Linear Regression Model
BT  - Proceedings of the 2025 4th International Conference on Engineering Management and Information Science (EMIS 2025)
PB  - Atlantis Press
SP  - 239
EP  - 246
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-736-6_28
DO  - 10.2991/978-94-6463-736-6_28
ID  - Li2025
ER  -