Volume 35 Issue 10
Oct.  2010
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HUANG Xianyuan, ZHAI Guojun, SUI Lifen, HUANG Motao. Application of Least Square Support Vector Machine to Detecting Outliers of Multi-beam Data[J]. Geomatics and Information Science of Wuhan University, 2010, 35(10): 1188-1191.
Citation: HUANG Xianyuan, ZHAI Guojun, SUI Lifen, HUANG Motao. Application of Least Square Support Vector Machine to Detecting Outliers of Multi-beam Data[J]. Geomatics and Information Science of Wuhan University, 2010, 35(10): 1188-1191.
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Application of Least Square Support Vector Machine to Detecting Outliers of Multi-beam Data

  • 1Institute of Surveying and Mapping,Information Engineering University,66 Middle Longhai Road,Zhengzhou 450052,China;2Naval Institute of Hydrographic Surveying and Charting,40 Youyi Road,Tianjin 300061,China

Funds: 国家863计划资助项目(2007AA12Z326)；国家自然科学基金资助项目(40971306,40974010)
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  • Received Date: July 21, 2010
  • Revised Date: July 08, 2013
  • Published Date: October 04, 2010
    Graphical Abstract
    • Abstract
  • In order to solve the problem of trend surface conformation,a new method of constructing trend surface by LS-SVM is presented,and then outliers of Multi-beam data could be eliminated by the trend surface.In order to illuminate the correctness and rationality so a contrast between this method and the approach of trend surface filter.The theorem proves that the trend surface filter is the especial result of LS-SVM.The example shows that in the process of constructing trend surface by LS-SVM,the weight parameters could be adjusted,so the trend surface have the property of popular and steady,the outliers of Multi-beam data could be eliminated effectively.
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