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A novel integrated approach of relevance vector machine optimized by imperialist competitive algorithm for spatial modeling of shallow landslides

Dieu, Tien Bui and Shahabi, Himan and Shirzadi, Ataollah and Chapi, Kamran and Nhat, Duc Hoang and Binh, Thai Pham and Quang, Thanh Bui and Chuyen, Trung Tran and Panahi, Mahdi and Ahmad, Baharin and Saro, Lee (2018) A novel integrated approach of relevance vector machine optimized by imperialist competitive algorithm for spatial modeling of shallow landslides. Remote Sensing, 10 (10). ISSN 2072-4292

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Official URL: http://dx.doi.org/10.3390/rs10101538

Abstract

This research aims at proposing a new artificial intelligence approach (namely RVM-ICA) which is based on the Relevance Vector Machine (RVM) and the Imperialist Competitive Algorithm (ICA) optimization for landslide susceptibility modeling. A Geographic Information System (GIS) spatial database was generated from Lang Son city in Lang Son province (Vietnam). This GIS database includes a landslide inventory map and fourteen landslide conditioning factors. The suitability of these factors for landslide susceptibility modeling in the study area was verified by the Information Gain Ratio (IGR) technique. A landslide susceptibility prediction model based on RVM-ICA and the GIS database was established by training and prediction phases. The predictive capability of the new approach was evaluated by calculations of sensitivity, specificity, accuracy, and the area under the Receiver Operating Characteristic curve (AUC). In addition, to assess the applicability of the proposed model, two state-of-the-art soft computing techniques including the support vector machine (SVM) and logistic regression (LR) were used as benchmark methods. The results of this study show that RVM-ICA with AUC = 0.92 achieved a high goodness-of-fit based on both the training and testing datasets. The predictive capability of RVM-ICA outperformed those of SVM with AUC = 0.91 and LR with AUC = 0.87. The experimental results confirm that the newly proposed model is a very promising alternative to assist planners and decision makers in the task of managing landslide prone areas.

Item Type:Article
Uncontrolled Keywords:GIS, hybrid intelligence, imperialist competitive algorithm, relevance vector machine, shallow landslide, Vietnam
Subjects:G Geography. Anthropology. Recreation > G Geography (General)
G Geography. Anthropology. Recreation > GE Environmental Sciences
Divisions:Geoinformation and Real Estate
ID Code:86067
Deposited By: Yanti Mohd Shah
Deposited On:30 Aug 2020 16:53
Last Modified:30 Aug 2020 16:53

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