Kaustuv Mukherjee

Employment

Employment history is unavailable.

Education

Education history is unavailable.

Projects & Funding

Projects & funding information is unavailable.

Publications (14)

• Manifesting deep learning algorithms for developing drought vulnerability index in monsoon climate dominant region of West Bengal, India
  Theoretical and Applied Climatology 2023 DOI: 10.1007/s00704-022-04300-4
  +Save
• Prediction of groundwater nitrate concentration in a semiarid region using hybrid Bayesian artificial intelligence approaches
  Environmental Science and Pollution Research 2022 DOI: 10.1007/s11356-021-17224-9
  +Save
• Application of novel ensemble models and k-fold CV approaches for Land subsidence susceptibility modelling
  Stochastic Environmental Research and Risk Assessment 2022 DOI: 10.1007/s00477-021-02036-7
  +Save
• Hydrological and landscape dynamics of floodplain wetlands of the Diara region, Eastern India
  Ecological Indicators 2021 DOI: 10.1016/j.ecolind.2020.106961
  +Save
• Spatial assessment of drought vulnerability using fuzzy-analytical hierarchical process: a case study at the Indian state of Odisha
  Geomatics, Natural Hazards and Risk 2021 DOI: 10.1080/19475705.2020.1861114
  +Save
• Spatial Prediction of Groundwater Potentiality Mapping Using Machine Learning Algorithms
  Research Square 2021 DOI: 10.21203/rs.3.rs-303246/v1
  +Save
• Wetland habitat stability assessment in hydro-geomorphological (HGM) and surface water availability (SWA) conditions in a lower Gangetic floodplain region of Eastern India
  Ecological Indicators 2020 DOI: 10.1016/j.ecolind.2020.106842
  +Save
• Modeling Spatial Flood using Novel Ensemble Artificial Intelligence Approaches in Northern Iran
  Remote Sensing 2020 DOI: 10.3390/rs12203423
  +Save
• Evaluating the Efficiency of Different Regression, Decision Tree, and Bayesian Machine Learning Algorithms in Spatial Piping Erosion Susceptibility Using ALOS/PALSAR Data
  Land 2020 DOI: 10.3390/land9100346
  +Save
• Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, REPTree: A case study at the Gumani River Basin, India
  Science of The Total Environment 2020 DOI: 10.1016/j.scitotenv.2020.139197
  +Save