Biswajeet Pradhan

Research interests

Publications

• Novel hybrid intelligence models for flood-susceptibility prediction: Meta optimization of the GMDH and SVR models with the genetic algorithm and harmony search

  Journal of Hydrology · 2020 · https://doi.org/10.1016/j.jhydrol.2020.125423

• Fuzzy-metaheuristic ensembles for spatial assessment of forest fire susceptibility

  Journal of Environmental Management · 2020 · https://doi.org/10.1016/j.jenvman.2019.109867

• Flash flood susceptibility modelling using functional tree and hybrid ensemble techniques

  Journal of Hydrology · 2020 · https://doi.org/10.1016/j.jhydrol.2020.125007

• Comparison of machine learning models for gully erosion susceptibility mapping

  Geoscience Frontiers · 2019 · https://doi.org/10.1016/j.gsf.2019.11.009

• Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping

  Sensors · 2018 · https://doi.org/10.3390/s18113777

• Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms

  Sensors · 2018 · https://doi.org/10.3390/s18082464

• Spatial prediction of landslide susceptibility using data mining-based kernel logistic regression, naive Bayes and RBFNetwork models for the Long County area (China)

  Bulletin of Engineering Geology and the Environment · 2018 · https://doi.org/10.1007/s10064-018-1256-z

• Landslide susceptibility mapping using J48 Decision Tree with AdaBoost, Bagging and Rotation Forest ensembles in the Guangchang area (China)

  CATENA · 2018 · https://doi.org/10.1016/j.catena.2018.01.005

• A novel hybrid integration model using support vector machines and random subspace for weather-triggered landslide susceptibility assessment in the Wuning area (China)

  Environmental Earth Sciences · 2017 · https://doi.org/10.1007/s12665-017-6981-2

• GIS-based modeling of rainfall-induced landslides using data mining-based functional trees classifier with AdaBoost, Bagging, and MultiBoost ensemble frameworks

  Environmental Earth Sciences · 2016 · https://doi.org/10.1007/s12665-016-5919-4

• A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility

  CATENA · 2016 · https://doi.org/10.1016/j.catena.2016.11.032

• A comparative study of different machine learning methods for landslide susceptibility assessment: A case study of Uttarakhand area (India)

  Environmental Modelling & Software · 2016 · https://doi.org/10.1016/j.envsoft.2016.07.005

• A hybrid artificial intelligence approach using GIS-based neural-fuzzy inference system and particle swarm optimization for forest fire susceptibility modeling at a tropical area

  Agricultural and Forest Meteorology · 2016 · https://doi.org/10.1016/j.agrformet.2016.11.002

• Hybrid artificial intelligence approach based on neural fuzzy inference model and metaheuristic optimization for flood susceptibilitgy modeling in a high-frequency tropical cyclone area using GIS

  Journal of Hydrology · 2016 · https://doi.org/10.1016/j.jhydrol.2016.06.027

• Spatial prediction of rainfall-induced landslides for the Lao Cai area (Vietnam) using a hybrid intelligent approach of least squares support vector machines inference model and artificial bee colony optimization

  Landslides · 2016 · https://doi.org/10.1007/s10346-016-0711-9

• Rainfall-induced landslide susceptibility assessment at the Chongren area (China) using frequency ratio, certainty factor, and index of entropy

  Geocarto International · 2016 · https://doi.org/10.1080/10106049.2015.1130086

• Comparison of four kernel functions used in support vector machines for landslide susceptibility mapping: a case study at Suichuan area (China)

  Geomatics Natural Hazards and Risk · 2016 · https://doi.org/10.1080/19475705.2016.1250112

• Spatial prediction of landslide hazard at the Yihuang area (China) using two-class kernel logistic regression, alternating decision tree and support vector machines

  CATENA · 2015 · https://doi.org/10.1016/j.catena.2015.05.019

• 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

  Landslides · 2015 · https://doi.org/10.1007/s10346-015-0557-6

• Flood susceptibility mapping using a novel ensemble weights-of-evidence and support vector machine models in GIS

  Journal of Hydrology · 2014 · https://doi.org/10.1016/j.jhydrol.2014.03.008

• Spatial prediction of landslide hazards in Hoa Binh province (Vietnam): A comparative assessment of the efficacy of evidential belief functions and fuzzy logic models

  CATENA · 2012 · https://doi.org/10.1016/j.catena.2012.04.001

• Landslide Susceptibility Assessment in Vietnam Using Support Vector Machines, Decision Tree, and Naïve Bayes Models

  Mathematical Problems in Engineering · 2012 · https://doi.org/10.1155/2012/974638

• A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS

  Computers & Geosciences · 2012 · https://doi.org/10.1016/j.cageo.2012.08.023

• Landslide susceptibility assessment in the Hoa Binh province of Vietnam: A comparison of the Levenberg–Marquardt and Bayesian regularized neural networks

  Geomorphology · 2012 · https://doi.org/10.1016/j.geomorph.2012.04.023

• Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam

  Natural Hazards · 2012 · https://doi.org/10.1007/s11069-012-0510-0

• Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran

  Natural Hazards · 2012 · https://doi.org/10.1007/s11069-012-0217-2

• Landslide susceptibility mapping at Hoa Binh province (Vietnam) using an adaptive neuro-fuzzy inference system and GIS

  Computers & Geosciences · 2011 · https://doi.org/10.1016/j.cageo.2011.10.031

• Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models

  Landslides · 2006 · https://doi.org/10.1007/s10346-006-0047-y

Current projects

No projects listed.