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Biswajeet Pradhan
Researcher at University of Technology, Sydney
Publications - 810
Citations - 47157
Biswajeet Pradhan is an academic researcher from University of Technology, Sydney. The author has contributed to research in topics: Landslide & Computer science. The author has an hindex of 98, co-authored 735 publications receiving 32900 citations. Previous affiliations of Biswajeet Pradhan include Symbiosis International University & IT University.
Papers
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A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS
TL;DR: In this paper, three different approaches such as decision tree (DT), support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) were compared for landslide susceptibility mapping at Penang Hill area, Malaysia.
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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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Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models
Saro Lee,Biswajeet Pradhan +1 more
TL;DR: In this paper, the authors evaluated the landslide hazards at Selangor area, Malaysia, using Geographic Information System (GIS) and Remote Sensing (RS) using aerial photograph interpretation and field survey.
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Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling
Biswajeet Pradhan,Saro Lee +1 more
TL;DR: The distribution of landslide susceptibility zones derived from ANN shows similar trends as those obtained by applying in GIS-based susceptibility procedures by the same authors (using the frequency ratio and logistic regression method) and indicates that ANN results are better than the earlier method.
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Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran
TL;DR: In this paper, the authors used fuzzy logic and analytical hierarchy process (AHP) models to produce landslide susceptibility maps of a landslide-prone area (Haraz) in Iran.