Research on Cost Determination Technology for Power Grid Engineering Based on Bayesian Deep Learning Network Potential Impact Factor Mining

Tianmina Wu ()
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Tianmina Wu: Zhengzhou University, School of Water Conservancy and Civil Engineering

A chapter in Proceedings of the 2023 4th International Conference on Management Science and Engineering Management (ICMSEM 2023), 2024, pp 840-847 from Springer

Abstract: Abstract The cost of power grid project is a multivariable and highly nonlinear problem. With the continuous expansion of the investment scale, the factors affecting the project cost are complex, diversified, volatility and other characteristics, and the single prediction model is often not comprehensive enough. In view of this, this paper excavates out the potential impact factor of project cost based on artificial neural network learning, which has a certain self-learning, adaptive ability, is a high accuracy, wide applicability of power grid engineering cost determination model, has high value, can further improve the efficiency of power grid enterprises.

Keywords: Power grid engineering; Bayesian deep learning network; cost determination technology (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-256-9_84

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