Prediction of Dam Settlement Using Metabolism BP Neural Network and Markov Chain

WAN Chen; LI Jian-feng; ZHAO Yong; ZHANG Jin-long

doi:10.11988/ckyyb.20140310

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Journal of Changjiang River Scientific Research Institute ›› 2015, Vol. 32 ›› Issue (10) : 23-27,32. DOI: 10.11988/ckyyb.20140310

ENGINEERING SAFETY AND DISASTER PREVENTION

Prediction of Dam Settlement Using Metabolism BP Neural Network and Markov Chain

WAN Chen^1,2,LI Jian-feng¹,ZHAO Yong² ,ZHANG Jin-long³

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Abstract

A dam settlement prediction model integrating BP neural network model and Markov chain prediction was built in this paper. Through emulating the training samples, rolling prediction for the settlement displacement time series was performed by the metabolism-improved BP neural network algorithm. Furthermore, Markov chain was used to correct its random disturbance and the prediction results were improved. This model was applied to the settlement displacement timing prediction of Changzhou dam lock control building. The result shows that the model has high prediction accuracy and good reliability. It improves the long-term prediction ability, and provides an effective method for dam settlement prediction.

Key words

settlement prediction / BP neural network / Markov chain / dam monitoring / Changzhou water power junction

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WAN Chen ,LI Jian-feng ,ZHAO Yong ,ZHANG Jin-long. Prediction of Dam Settlement Using Metabolism BP Neural Network and Markov Chain[J]. Journal of Changjiang River Scientific Research Institute. 2015, 32(10): 23-27,32 https://doi.org/10.11988/ckyyb.20140310

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