||Cost estimation of high performance concrete (hpc) high-rise commercial buildings by neural networks
||Fang C F, Froese T
||Neural network approach is applied to establish relationships between thequantities/cost of the concrete/formwork, which is required for the structuralelements of tall buildings using high performance concrete (HPC), and thedesign variables. Hybrid and hierarchical strategies are proposed for the costestimation, where the feed-forward networks are adopted. After training, theneural networks are utilized to predict automatically the quantities/cost ofHPC wall-frame structures in tall commercial buildings. Verifications areconducted with respect to various sets of the design parameters and acomprehensive discussion is given.
|Year of publication:
Fang C F, Froese T (1999).
Cost estimation of high performance concrete (hpc) high-rise commercial buildings by neural networks. Lacasse M A, Vanier D J (ed.); Information technology in construction, volume 4, ISBN 0-660-17743-9; Vancouver, May 30 - June 3, Canada (ISSN: 2706-6568),