Application Of Wavelet Theory To The Denoising And The Combinatorial Predetermination For Landslide

Landslide calamity bring out great loss to the people's life and asset.According to the preliminary statistics, the annual economic losses of our country are up to 200 billion yuan that the landslide and collapse caused.The area threatened by landslide accounts for 1/4 or 1/5 of the area of national land, landslide activity enter new activeness issue on a large scale in recent years,these landslide once happen,will bring unestimated losses.but if we can accurately forecast the time of the landslide 's happenning ,then wo can take steps to reduce the losses that caused by it to fewest.For these,this thesis has launched research to two key problems existing while landslide forecasting,it is how to effectively cull the pretended noise that affect the accuracy of landslide forecasting,and how to synthesize a generalized information in many predicting model. In the course of studying,author introduct the wavelet theory,and apply wavelet denoising method to denosing for landslide displacement monitor curve,and wavelet neural network to setting up landslide combination forecast model.The thesis discuss these problem:(1) Analyze the theory of wavelet denosing,and the different peculiarity under the wavelet transform between the signal and the noise ;(2)Two wavelet denoising methods are introduced here ------the nonlinearwavelet threshold denoising method and the wavelet transform modulus maxima method.these methods are used to remove the noise from the landslide data respectively;(3) The frame of wavelet neural network,and the learning method of the adaptive...