The neural network based on the deep learning theory has a profound theoretical basis and broad application prospects in the field of bridge structure damage identification. The comparison and analysis are made from three aspects of input vector, finite element model and neural network, which provides reference for further research on neural network in bridge structure damage identification. Through analysis, it is found that the ability of neural network to extract relevant information can be effectively improved by selecting the finite element model or the original data obtained in the actual situation as far as possible for the input vector. When the stress of bridge structure is simple, neural network with shallow layers and simple network structure can be selected. When the stress of bridge structure is complex, the neural network model with strong complexity should be selected first.
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