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Cheng, S., Sui, B.B., Shen, Y. and Wang, T. (2015) Study on Prediction of Surface Subsidence in Mining Area Based on BP Neural Network. Mapping and Geospatial Information, No. 3, 18-20. (In Chinese)

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• TITLE: Analysis and Prediction of Foundation Settlement of High-Rise Buildings under Complex Geological Conditions

  AUTHORS: Jihui Ding, Bingjun Li, Erxia Du, Weiyu Wang, Tuo Zhao

  KEYWORDS: Complex Geological Conditions, Settlement Law, Settlement Prediction, The BP Neural Network

  JOURNAL NAME: World Journal of Engineering and Technology, Vol.5 No.3, July 20, 2017

  ABSTRACT: Based on an example of a project in Tangshan, the high-rise buildings are built in karst area and mined out affected area which is treated by high pressure grouting, and foundation is adopted the form of pile raft foundation. By long-term measured settlement of high-rise buildings, It is found that foundation settlement is linear increase with the increase of load before the building is roof-sealed, and the settlement increases slowly after the building is roof-sealed, and the curve tends to converge, and the foundation consolidation is completed. The settlement of the foundation is about 80% - 84% of the total settlement before the building is roof-sealed.Three layer BP neural network model is used to predict the settlement in the karst area and mined affected area.Compared with the measured data, the relative difference of the prediction is 0.91% - 2.08% in the karst area, and is 0.95% - 2.11% in mined affected area. The prediction results of high precision can meet the engineering requirements.