Resistance Capacity Estimation for Confined Concrete Column and Anchorage Zone Based on Neural Network
A detailed study of the capabilities of artificial neural networks to predict resistance capacity in confined concrete structures is presented. This paper includes the definition of the architecture for a three layer backpropagation neural network, that processes the changes in the confinement effect of the reinforced concrete columns and a cross-section under concentrated load, due to quantity of transverse reinforcement, to the volume of the surrounding concrete and even to the stiffness of bearing plate. The network was trained and checked with a series of experimentally measured data and the results obtained show it is a feasible and acceptable method for simulating a complex stress state.
Canfeng Li Ionman Cheong
Lands, Public Works and Transports Department Government of Macao SAR, China
国际会议
8th International Conference on Neural Information Processing(ICONIP 2001)(第八届国际神经信息处理大会)
上海
英文
1619-1624
2001-11-14（万方平台首次上网日期，不代表论文的发表时间）