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- W2360900821 abstract "Using the nature of good time-frequency localization of wavelet transform and the self-learning function of neural networks,a combined freeway high filling subgrade settlement prediction model with S-Growth Model is established,based on wavelet neural network.The model is based on Real-time monitoring data,avoiding the calculation of various human factors.Through Ru-Chen freeway K59+375～K59+445 embankment settlement on-site monitoring data of high learning,prediction and testing,and with S-Growth Model and BP neural network prediction,results show that combined model of wavelet neural network prediction are accurate and consistent with the actual situation." @default.
- W2360900821 created "2016-06-24" @default.
- W2360900821 creator A5069949094 @default.
- W2360900821 date "2010-01-01" @default.
- W2360900821 modified "2023-09-24" @default.
- W2360900821 title "Combined forecasting model based on wavelet neural network for prediction of high fill subgrade settlement" @default.
- W2360900821 hasPublicationYear "2010" @default.
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