A comparison of Support Vector Machines and Bayesian algorithms for landslide susceptibility modelling |
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| Authors: | Binh T Pham Indra Prakash Khabat Khosravi Kamran Chapi Phan T Trinh Trinh Q Ngo |
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| Institution: | 1. Department of Geotechnical Engineering, University of Transport Technology, Thanh Xuan, Hanoi, Vietnam;2. Department of Science &3. Technology, Bhaskarcharya Institute for Space Applications and Geo-Informatics (BISAG), Government of Gujarat, Gandhinagar, India;4. Department of Watershed Management Engineering, Faculty of Natural Resources, Sari Agricultural Science and Natural Resources University, Sari, Iran;5. Department of Rangeland and Watershed Management, Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran;6. Institute of Geological Sciences, Vietnam Academy of Sciences and Technology, Dong da, Hanoi, Vietnam;7. Science Technology and International Cooperation Department, University of Transport Technology, Thanh Xuan, Hanoi, Vietnam |
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| Abstract: | AbstractIn this study, the main goal is to compare the predictive capability of Support Vector Machines (SVM) with four Bayesian algorithms namely Naïve Bayes Tree (NBT), Bayes network (BN), Naïve Bayes (NB), Decision Table Naïve Bayes (DTNB) for identifying landslide susceptibility zones in Pauri Garhwal district (India). First, landslide inventory map was built using 1295 historical landslide data, then in total sixteen influencing factors were selected and tested for landslide susceptibility modelling. Performance of the model was evaluated and compared using Statistical based index methods, Area under the Receiver Operating Characteristic (ROC) curve named AUC, and Chi-square method. Analysis results show that that the SVM has the highest prediction capability, followed by the NBT, DTNBT, BN and NB, respectively. Thus, this study confirms that the SVM is one of the benchmark models for the assessment of susceptibility of landslides. |
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| Keywords: | Naïve Bayes Trees Bayes network Naïve Bayes Decision Table Naïve Bayes Support Vector Machines |
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