Reliability Study of Pre-stressed Concrete Continuous Girder Bridges Based on Neural Network and Improved JC Algorithms
Wang Changcai;Department of Civil Engineering,Anhui Communications Vocational and Technical College;
It is difficult to solve the reliability of the pre-stressed concrete continuous girder bridges because of non-explicit limit state function. The BP neural network and improved JC algorithms are applied into analyzing the reliability of prestressed concrete continuous girder bridges. Firstly,using BP neural network to fit the structural performance function,making the highly nonlinear limit state equation show and then the improved JC method was used to globally search checking points and calculate the reliability index,and the efficiency and accuracy of the method are verified by numerical examples.And a pre-stressed concrete continuous girder bridge reliability index were calculated. The calculation and analysis results showed that the BP neural network and improved JC algorithms compensated the deficiency of the traditional reliability analysis methods,improved the calculation accuracy,provided a new thought and means for the research on the reliability of bridge structure,and well applied to the reliability analysis of pre-stressed concrete continuous girder bridges.
【CateGory Index】： U441;U446