径向基函数(RBF)神经网络在桥梁减震设计中的应用仿真

本文将人工智能理念引入桥梁结构的减震设计中,在对阻尼器参数进行参数分析的基础上,利用径向基函数(RBF)神经网络建立阻尼器参数与桥梁结构地震反应之间的映射关系,以帮助进行阻尼器参数的合理选定。同时,桥梁工程师可利用这一映射关系自行分析实际阻尼器性能参数的误差对结构地震反应的影响。本文最后通过工程实例,验证了人工神经网络算法在桥梁减震设计中应用的可能性和可靠性。

The Application of RBF Neural Network to Seismic Design of Bridges

The artificial intelligent algorithm is introduced into seismic design of bridges. Based on the right amount parameter analysis for fluid viscous damper, the mapping relations between the damper parameters and seismic responses of a bridge are established using the artificial intelligent algorithm, and then the reasonable damper parameters can be determined. Further, bridge engineers may analyze the influence of actual damper parameter errors on the seismic responses of bridges by themselves using these mapping relations. Finally, the application possibility and the reliability of the artificial intelligent algorithm to seismic design of bridges have been confirmed through a bridge example.