Investment Probabilistic Interval Estimation for Construction Project Using the Hybrid Model of SVR and GWO

Chen, Xiaobo; Zhang, Yuanyuan; Zhao, Binyan; Yang, Shuting

doi:10.1061/(asce)co.1943-7862.0002032

Cited by 2 publications

(1 citation statement)

References 41 publications

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“…The experimental results of the SD model proposed in this paper were compared with the experimental results of other high-speed railway intelligent construction investment estimation models that can be found in the related literature, i.e., the grey-wolf optimizer-support vector machine (GWO-SVM) estimation model [19] and the improved backpropagation neural network (BPNN) prediction model [20], and the specific data are shown in Table VIII. The error rate in Table VIII is the error between the two-year cumulative investment estimation and the actual investment, and it was seen that the error rate of this model was 1.83%, which was smaller other estimation models.…”

Section: Model Simulation and Results Analysismentioning

confidence: 99%

Research on the Derivative Rule and Estimation Methods of Intelligent High-Speed Railway Investment Estimation

Meng¹,

Meng²,

Xiao-chen³

2023

IJACSA

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Taking the investment estimation of intelligent construction of high-speed railway as the research object, based on the historical data of investment of similar high-speed railway projects, this paper builds an explanatory structure model, establishes an system dynamic (SD) model of investment estimation of intelligent construction of high-speed railway, and puts forward suggestions for supplementing the labor value theory and improving the value-added tax. The paper carries out in-depth research and analysis in the following aspects: 1) the list of influencing factors for investment estimation of intelligent construction of high-speed railway in the feasibility study stage is constructed, and the interpretative structural model (ISM) is constructed to sort out the relationship between the influencing factors; 2) the SD model of intelligent construction cost estimation of high-speed railway is established to improve the accuracy of investment estimation of intelligent high-speed railway construction; 3) put forward suggestions and schemes for improving investment estimation content of intelligent construction of high-speed railway under high intelligence; 4) improve and supplement the labor value theory and the valueadded tax base.

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Section: Model Simulation and Results Analysismentioning

confidence: 99%