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What is Machine Learning for Building Cost Optimization about?

This study presents a machine learning framework for the efficient estimation and optimization of building costs, utilizing a dataset of 10,000 building configurations. The research demonstrates that models like Artificial Neural Network (ANN), Gradient Boosting, and XGBoost can achieve up to 99% accuracy in cost estimation, significantly enhancing operational efficiency and competitiveness for construction companies. Additionally, the optimized costs derived from this study are 7% lower than actual data, s

Author

Gini Mwiinga

Language

EN