DSCostPred: a double-stacking model for construction cost prediction.

ABSTRACT: The prediction of construction project cost plays a core role in engineering construction projects. However, the current prediction involves a multi-dimensional and dynamically variable system, and each major category can be further subdivided into many specific factors. Meanwhile, variables' relationships present a complex network of nonlinearity and interaction, which seriously affected the prediction accuracy. To solve this problem, we proposed a dual-stacking construction cost prediction method based on variable stacking and model stacking (DSCostPred). This method emphasizes that classifying variables and applying different algorithms respectively can avoid the impact of variables' functional differences. First, the variables are pre-classified to avoid mutual interference among them.

SUBMITTER: Liu CP 

PROVIDER: S-EPMC12834979 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature