A formwork method selection model based on boosted decision trees in tall building construction

In tall building construction with reinforced concrete structures, the appropriate selection of the formwork method is a crucial factor in successful project completion. The selected formwork method significantly influences the project duration and cost as well as subsequent activities. However, in practice, this selection has depended mainly on the subjective and intuitive opinions of practitioners with restricted experience. Therefore, we propose a formwork method selection model based on boosted decision trees to assist the practitioner's decision making. To evaluate its performance, the proposed model was compared with an artificial neural network model and a decision tree model. The results showed that the proposed model was slightly more accurate than the others in the selection of the formwork method. Moreover, the result also demonstrated the advantages of the new method, i.e., single parameter setting, accuracy and stability improvement, and a comprehensible process in decision making.

► In this study, we propose a formwork method selection model.
► We construct the proposed model using boosted decision trees.
► The model showed slightly better performance than the others.
► Moreover, the model also demonstrated the advantages of the new approach.