机构地区: 长沙理工大学桥梁与结构工程学院
出 处: 《长沙交通学院学报》 2004年第4期65-69,共5页
摘 要: 利用RBF神经网络预测预应力高强混凝土简支T梁极限承载力。重点讨论了RBF神经网络的结构和算法,通过对预测结果进行分析比较,证明此方法在预应力高强混凝土简支T梁极限承载力的预测中具有实用价值。 Neural network has strong nonlinear mapping function. The authors pedict ultimate load (capacity) of simply-supported T beam with prestressed high strength concrete by means of RBF (Radial Basis (Function)) neural network. Structure and algorithm of RBF neural networks are emphasized in the (discussion). The method has practical meanings in predicting ultimate load capacity of simply-supported T beam with prestressed high strength concrete by analyzing and contrasting the obtained results.