The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XL-1/W5
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 301–305, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-301-2015
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 301–305, 2015
https://doi.org/10.5194/isprsarchives-XL-1-W5-301-2015

  11 Dec 2015

11 Dec 2015

AN EFFECTIVE HYBRID SUPPORT VECTOR REGRESSION WITH CHAOS-EMBEDDED BIOGEOGRAPHY-BASED OPTIMIZATION STRATEGY FOR PREDICTION OF EARTHQUAKE-TRIGGERED SLOPE DEFORMATIONS

A. A. Heidari1, S. S. Mirvahabi1, and S. Homayouni2 A. A. Heidari et al.
  • 1School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Iran
  • 2Department of Geography, Environmental Studies and Geomatics, University of Ottawa, Canada

Keywords: Earthquake, Support Vector Regression, Biogeography-based Optimisation, Displacement, Hazard

Abstract. Earthquake can pose earth-shattering health hazards to the natural slops and land infrastructures. One of the chief consequences of the earthquakes can be land sliding, which is instigated by durable shaking. In this research, an efficient procedure is proposed to assist the prediction of earthquake-originated slope displacements (EIDS). New hybrid SVM-CBBO strategy is implemented to predict the EIDS. For this purpose, first, chaos paradigm is combined with initialization of BBO to enhance the diversification and intensification capacity of the conventional BBO optimizer. Then, chaotic BBO is developed as the searching scheme to investigate the best values of SVR parameters. In this paper, it will be confirmed that how the new computing approach is effective in prediction of EIDS. The outcomes affirm that the SVR-BBO strategy with chaos can be employed effectively as a predicting tool for evaluating the EIDS.