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Inge Revhaug
Researcher at Norwegian University of Life Sciences
Publications - 24
Citations - 4187
Inge Revhaug is an academic researcher from Norwegian University of Life Sciences. The author has contributed to research in topics: Landslide & Support vector machine. The author has an hindex of 18, co-authored 24 publications receiving 3247 citations.
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Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree
TL;DR: This study introduces a framework for training and validation of shallow landslide susceptibility models by using the latest statistical methods and demonstrates the benefit of selecting the optimal machine learning techniques with proper conditioning selection method in shallow landslide susceptible mapping.
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A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran.
Khabat Khosravi,Binh Thai Pham,Kamran Chapi,Ataollah Shirzadi,Himan Shahabi,Inge Revhaug,Indra Prakash,Dieu Tien Bui +7 more
TL;DR: Results show that the ADT model has the highest prediction capability for flash flood susceptibility assessment, followed by the NBT, the LMT, and the REPT, respectively.
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Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naïve Bayes Models
TL;DR: In this paper, the results of three data mining approaches, the support vector machines (SVM), decision tree (DT), and Naive Bayes (NB) models for spatial prediction of landslide hazards in the Hoa Binh province (Vietnam) were investigated and compared.
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Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS
TL;DR: Results of this study show that landslide susceptibility mapping in the Hoa Binh province of Vietnam using the ANFIS approach is viable and the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.
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Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): A comparative assessment of the efficacy of evidential belief functions and fuzzy logic models
TL;DR: Evaluated and compared the results of evidential belief functions and fuzzy logic models for spatial prediction of landslide hazards in the Hoa Binh province of Vietnam, using geographic information systems show that all the models have good prediction capabilities.