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《Mining Safety & Environmental Protection》 2009-01
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Comparative Study on Surface Subsidence Prediction Based on BP-ANN Model

FAN Hong-dong,DENG Ka-zhong,WEI Hao  
Based on comprehensive analysis of the factors influencing surface subsidence,a prediction model for surface subsidence was established by different methods of back propagation artificial neural network(BP-ANN).A large amount of data obtained at observation stations in a mining field was used for training and performance test of BP-ANN models,and comparison and analysis on these models were made. The results indicated that it is much more reasonable to use BP-ANN model to predict the mining subsidence.The method limited artificial factors during the prediction,simplified the complex problems and made the solution more reasonable and creditable.So,it has a certain application value.
【Fund】: “十一五”国家科技支撑计划重点项目(2006BAC09B001);; 国家自然科学基金项目(40772191)
【CateGory Index】: TD325.4
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Chinese Journal Full-text Database 1 Hits
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