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《Journal of Hubei University for Nationalities(Natural Science Edition)》 2018-01
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Grey Relational BP Neural Network Based on Wavelet Denoising in the Application of Dam Settlement Deformation Monitoring

DAI Liwen;WANG Shengping;WU Meng;Faculty of Geomatics,East China University of Technology;Key Laboratory of Watershed Ecology and Geographical Environment Monitoring;  
Aiming at the disturbance of many factors in dam deformation,a grey relational BP neural network model based on wavelet denoising is proposed in this paper.Firstly,wavelet threshold denoising method is used for data processing,and then the grey relational analysis is used to calculate and analyze the factors affecting the deformation monitoring of dam settlement,and obtain the influence factors of greater relevance.A model is established by combining grey relational analysis and BP neural network,and finally it is compared with the grey BP neural network without data processing and Calman filter model to obtain the conclusion.The experimental results show that the prediction accuracy and reliability of the grey relational BP neural network model are improved after the wavelet denoising data processing.Using grey relational analysis can deal with a large number of input variables,without subjective screening,and then increase the adaptive ability of BP neural network,the prediction results than other single model closer to the final measured with higher accuracy and reliability.
【Fund】: 国家自然科学基金项目(41206078);; 江西省数字国土重点实验室开放基金项目(DLLJ201510);; 江西省自然科学基金项目(20142BAB217025)
【CateGory Index】: TV698.1
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