The Influence of Optimized Train Samples on Elimination of Sounding Outliers in the LS-SVM Arithmetic
Hongzhou Chai · Acta Geodaetica et Cartographica Sinica · 2011
As validating the trend filter is the special result to the LS-SVM arithmetic,the sounding outliers are eliminated by the seafloor surface which constructed by LS-SVM.In order to solve the sparseness of LS-SVM results and restrain the influence of the sample-outliers,a new method of optimized samples by part samples center distance is presented.Some practical multi-beam data is chosen to verify the correctness and rationality of the new method.The example shows that on the ground of the optimized train samples,the reasonable seafloor surface could be constructed by LS-SVM arithmetic,and then the outliers of multi-beam data could be eliminated effectively.