Construction cost prediction model for agricultural water conservancy engineering based on BIM and neural network

Construction cost prediction model for agricultural water conservancy engineering based on BIM and neural network

Abstract Due to the complex construction conditions, long work cycles, and high uncertainty inherent in agricultural water conservancy projects, accurate construction cost prediction is crucial for investment decisions. This study presents an innovative cost prediction model for these projects, inte...

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Bibliographic Details
Main Authors: Kun Han, Tieliang Wang, Wenhe Liu, Chunsheng Li, Xiaochen Xian, Yingying Yang
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Agricultural water conservancy engineering
Construction cost
BIM technology
Sparrow search algorithm (SSA)
Grey BP neural network (PGNN)
Online Access:https://doi.org/10.1038/s41598-025-10153-4
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https://doi.org/10.1038/s41598-025-10153-4

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