Using the FA-NAR Dynamic Neural Network Model and Big Data to Monitor Dam Safety

Abstract

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In view of the dynamics of the dam safety monitoring data, the sensitivity to time and space, and the nonlinearity, it has been proposed to use the firefly algorithm to search to determine the delay order and the number of hidden layer units and combine them with nonlinear autoregressive algorithms. The algorithms are combined to obtain the FA-NAR algorithm dam deformation prediction model, which is compared with the traditional BP algorithm prediction results, combined with the Xiaolangdi dam deformation monitoring data for prediction, and the dam deformation data predicted by the dynamic neural network have a better convergence effect and a more accurate prediction result. It provides a certain reference basis for perfecting dam safety monitoring.

Keywords

• dig data
• FA-NAR dynamic neural network
• dam safety
• model integration
• monitor safety