Cost estimation of high performance concrete (hpc) high-rise commercial buildings by neural networks

摘要: Neural network approach is applied to establish relationships between the quantities/cost of the concrete/formwork, which required for structural elements tall buildings using high performance concrete (HPC), and the design variables. Hybrid hierarchical strategies are proposed cost estimation, where feed-forward networks adopted. After training, the neural utilized predict automatically quantities/cost of HPC wall-frame structures in commercial buildings. Verifications are conducted with respect various sets design parameters a comprehensive discussion given.