Abstract: Economic risk control is pivotal to the success of engineering projects. Traditional risk assessment methods often fall short in handling the high-dimensional, nonlinear, and strongly correlated risk factors prevalent in modern large-scale projects. To address these limitations, this study constructs an engineering economic risk management platform based on the BO-GBM model, which integrates Bayesian Optimization (BO) with a Gradient Boosting Machine (GBM). The platform employs a systematically constructed four-dimensional feature system encompassing 28 indicators across project ontology, market environment, execution process, and risk association dimensions. A rolling time window strategy is adopted for dynamic model training. Experimental validation on a dataset of 327 projects demonstrates the superior performance of the BO-GBM model: for classification tasks, it achieves an AUC of 0.927 and a recall rate of 91.3%, outperforming the standard GBM by 17.5 percentage points in recall; for regression tasks (cost deviation prediction), it attains an RMSE of 83,200 RMB and reduces the MAPE to 9.7%, surpassing mainstream baseline models. The platform's layered architecture (data, model, service, application layers) enables efficient risk identification and early warning: the time required for risk identification in large projects is drastically reduced from 42.6 hours to 0.52 hours, representing an 81.9-fold efficiency gain; the average single prediction response time is below 127 milliseconds, with a P95 response time of 427 milliseconds under 500 concurrent users; the early warning accuracy reaches 72.5%, with high-risk warnings issued up to 28 days in advance for cost risks and 42 days for schedule risks.

Chaojian Wang and Die Liu. “Construction and Characteristics of an Engineering Economic Risk Management Platform Based on the BO-GBM Model”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.10 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0161010

@article{Wang2025,
title = {Construction and Characteristics of an Engineering Economic Risk Management Platform Based on the BO-GBM Model},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0161010},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0161010},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {10},
author = {Chaojian Wang and Die Liu}
}