基于大数据的地铁全线建设投资智能控制研究

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Abstract Research purposes: Due to the complexity, sequence, space and openness of investment consumption factors in subway construction projects, the existing fixed investment control mode has far failed to meet the requirements of investment randomness and nonlinear evolution, and it is urgent to reform the subway investment control management mode. Therefore, this paper comprehensively uses BIM, Python technology, fuzzy mathematics, BP neural network, acquired value theory and PDCA cycle method to build an intelligent prediction and control method for subway construction investment.
Research conclusions: (1) The basic database of subway construction investment is established, and the cause and countermeasure database of subway project investment is constructed. (2) Using SPSS factor analysis, rough set theory, fuzzy mathematics combined with BP neural network, the overall construction objective of the whole line is obtained. (3) Integrated PDCA cycle and acquired value theory carry out dynamic investment optimization control for key control projects, significantly improving the overall management efficiency and level of the project. (4) The computer aided intelligent control software for subway construction investment was established and applied in Chengdu subway construction example. (5) The research results can provide a feasible plan for the investment control of the entire subway line construction.

Key words： construction of the entire subway line BP neural network investment intelligent forecasting intelligent control

Received: 22 January 2024

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U477

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	Articles by authors
	DUAN Xiaochen
	YANG Jing
	WANG Hui
	WANG Dan

Cite this article:

DUAN Xiaochen,YANG Jing,WANG Hui, et al. Research on Intelligent Control of Subway Construction Investment Based on Big Data[J]. Journal of Railway Engineering Society, 2024, 41(11): 118-123.

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https://tdgcxb.crec.cn/EN/ OR https://tdgcxb.crec.cn/EN/Y2024/V41/I11/118

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