Deep mining model of capital construction cost data based on confidence network

Li Ma; Liping Sun; Xuefei Zhang; Xiaohong Liao; Lin Yang; Lingfeng Xu

doi:10.1117/12.2631120

18 March 2022 Deep mining model of capital construction cost data based on confidence network

Li Ma, Liping Sun, Xuefei Zhang, Xiaohong Liao, Lin Yang, Lingfeng Xu

Proceedings Volume 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021); 121682A (2022) https://doi.org/10.1117/12.2631120
Event: International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 2021, Harbin, China

Abstract

Making full use of the historical data of the construction project and accurately and quickly predicting the project cost, can provide fast and reliable data support for the feasibility study, investment decision-making, quota design, scheme comparison and bidding decision-making of the project. Strengthening the accumulation and application of project cost data is not only the direction of the development of project cost information in China, but also the requirement of the State Council to promote the sustainable and healthy development of the construction industry. The principle and structure of deep confidence network are analyzed, and the confidence network model and RBM training model are discussed. Through the analysis of the change trend of project cost, the results show that the factor affecting the change of project cost may be the rise of steel price.

Citation Download Citation

Li Ma, Liping Sun, Xuefei Zhang, Xiaohong Liao, Lin Yang, and Lingfeng Xu "Deep mining model of capital construction cost data based on confidence network", Proc. SPIE 12168, International Conference on Computer Graphics, Artificial Intelligence, and Data Processing (ICCAID 2021), 121682A (18 March 2022); https://doi.org/10.1117/12.2631120

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