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 …

To scientifically perform health monitoring and safety evaluation of bridges, a new bridge
safety evaluation method is proposed based on genetic algorithm and BP neural network …

With the rapid development of high-rise buildings, structural health testing has become a
research hotpot in the field of civil engineering. Effective and rapid identification of the …

Bridges play an important role in transportation, but because of overload and natural factors,
bridges will inevitably be damaged, which will affect traffic and even lead to major accidents …

Safety monitoring is an important part of bridge engineering construction and operation. At
present, there is room for promoting the health monitoring and evaluation of small and …

In last few years, big data and deep learning technologies have been successfully applied in
various fields of civil engineering with the great progress of machine learning techniques …

Traditional statistical pattern identification methods, such as artificial neural network and
support vector machine, have limited ability to identify minor damage of bridges. Deep …

English To improve the accuracy and anti-noise ability of the structural damage identification
method, a bridge damage identification method is proposed based on a deep belief network …

To solve the problem of poor anti-noise ability faced by traditional pattern recognition
methods in damage identification field, a bridge damage identification method based on …

Damage caused by sudden and specific loads such as earthquakes causes undesirable
changes in structural performance. Therefore, in recent years need for methods to identify …