基于人工神经网络的大坝变形分析与预报——以西津大坝27~#点的变形监测为例
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摘要
以MATLAB语言为基础,应用BP神经网络、逐步回归分析进行西津大坝27#点的变形分析与预报研究。在此基础上,进一步提出了逐步回归BP神经网络组合的预报方法,并探讨了3种方法的预报结果。研究表明,BP神经网络用于大坝变形分析与预报是可行的,所提出的逐步回归BP神经网络组合法提高了变形影响因子选择的科学性,在预报效果上,优于前两种方法。
On the basis of MATLAB programming language,BP neural network and stepwise regression are applied to predict the deformation at monitoring point No.27 of Xijin dam.Furthermore,the combination prediction method of BP network and stepwise regression is put forward and the prediction results of 3 methods are compared.The research shows that it is feasible to apply BP neural network to dam deformation analysis and prediction.In addition,the combination method improves the scientific quality to choice deformation factors.The combination method is prior to the method of stepwise regression in prediction result and it is worth to further study.
On the basis of MATLAB programming language,BP neural network and stepwise regression are applied to predict the deformation at monitoring point No.27 of Xijin dam.Furthermore,the combination prediction method of BP network and stepwise regression is put forward and the prediction results of 3 methods are compared.The research shows that it is feasible to apply BP neural network to dam deformation analysis and prediction.In addition,the combination method improves the scientific quality to choice deformation factors.The combination method is prior to the method of stepwise regression in prediction result and it is worth to further study.
引文
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[3]吴云芳,李珍照.大坝神经网络预报模型与大坝回归预报模型的比较[J].长江科学院院报,2003,20(2):50-53.WU Yun-fang,LI Zhen-zhao.Comparison between BPneural network model and statistical regression modelof dam[J].Journal of Yangtze River Scientific Re-search Institute,2003,20(2):50-53.
[4]吴秀娟,李征航.基于BP网络的大坝变形分析与预报[J].测绘信息与工程,2003,28(5):33-34.WU Xiu-juan,LI Zheng-hang.Analysis and predictionof dam deformation based on BP network[J].Journalof Geomatics,2003,28(5):33-34.
[5]方卫华.两类模型在大坝变形监测资料分析中的应用[J].广西水利水电,2004(4):54-58.FANG Wei-hua.Application of two types of models inanalysis of dam deformation monitoring data[J].GXWater Resources&Hydropower Engineering,2004(4):54-58.
[6]龚晶晶,蔡忠贤,谭述.BP神经网络在自喷井井底流压预测中的应用[J].世界地质,2006,25(2):191-195.GONG Jing-jing,CAI Zhong-xian,TAN Shu.Applica-tion of BP neural network for prediction of flowingbottom-hole pressure in flowing well[J].GlobleGeology,2006,25(2):191-195.
[7]赵丁选,崔功杰,陈宁,等.基于BP神经网络的工程车辆四参数自动变速控制[J].吉林大学学报:工学版,2008,38(5):1091-1094.ZHAO Ding-xuan,CUI Gong-jie,CHEN Ning,et al.Control system for four-parameter automatic transmis-sion of construction vehicle based on BP neural net-work[J].Journal of Jilin University:Engineering andTechnology Edition,2008,38(5):1091-1094.
[8]王炜,蒋春曦,张军,等.BP神经网络在地震综合预报中的应用[J].地震,1999,19(2):118-126.WANG Wei,JIANG Chun-xi,ZHANG Jun,et al.The application of BP neural network to comprehensiveearthquake prediction[J].Earthquake,1999,19(2):118-126.
[9]王晓蕾,王其霞,槐先锋.逐步回归模型在大坝监测中的应用[J].水科学与工程技术,2006(1):60-62.WANG Xiao-lei,WANG Qi-xia,HUAI Xian-feng.Ap-plication of stepwise regression model in dam monito-ring[J].Hydraulic Science and Engineering Technolo-gy,2006(1):60-62.
[10]葛哲学,孙志强.神经网络理论与MATLAB R2007实现[M].北京:电子工业出版社,2007.GE Zhe-xue,SUN Zhi-qiang.Neural networks theoryand the implementation of MATLAB R2007[M].Bei-jing:Publishing House of Electruonics Industry,2007.
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