Forecast of Highway Subgrade Settlement Based on Improved BP Neural Network


Forecast of Highway Subgrade Settlement Based on Improved BP Neural Network


Shengxiang Ma

China Academy of Safety Science and Technology, Beijing, China


Scientific Research and Reviews

In order to improve the feasibility and accuracy of the roadbed settlement prediction model, the factor analysis method is combined with the BP neural network method, and an improved BP neural network roadbed settlement prediction model is proposed. Select example data to test the improved BP neural network roadbed settlement prediction model. The test results: The relative average error of the 10 sets of training samples’ predicted and actual roadbed settlements was 4.287%, and the roads of five predicted samples The relative error of subgrade settlement is 1.79%, 1.93%, 6.62%, 7.19%, 4.05%, all less than 10%, which proves that the improved BP neural network prediction model has good prediction accuracy.


Keywords: Roadbed settlement; Factor analysis method; BP neural network; Simulation prediction


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How to cite this article:
Shengxiang Ma. Forecast of Highway Subgrade Settlement Based on Improved BP Neural Network. Scientific Research and Reviews, 2020; 13:118. DOI:10.28933/srr-2020-10-0105


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