Dieu Tien Bui

Active 2011–2024

137
Papers
26,110
Citations
83
h-index
131
i10-index

Citations

Citations per year for Dieu Tien Bui2004: 1 citations2008: 1 citations2011: 1 citations2012: 32 citations2013: 29 citations2014: 34 citations2015: 54 citations2016: 162 citations2017: 180 citations2018: 445 citations2019: 791 citations2020: 1,242 citations2021: 909 citations2022: 806 citations2023: 727 citations2024: 662 citations2025: 372 citations2026: 46 citations2005–2007: no citations, so these years are not shown2009–2010: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorChina: 1,416 citing papers, 22.9% of this breakdownIran: 430 citing papers, 7% of this breakdownUnited States: 402 citing papers, 6.5% of this breakdownIndia: 389 citing papers, 6.3% of this breakdownVietnam: 360 citing papers, 5.8% of this breakdownAustralia: 242 citing papers, 3.9% of this breakdownMalaysia: 197 citing papers, 3.2% of this breakdownSouth Korea: 196 citing papers, 3.2% of this breakdownSaudi Arabia: 147 citing papers, 2.4% of this breakdownCanada: 134 citing papers, 2.2% of this breakdownJapan: 122 citing papers, 2% of this breakdownUnited Kingdom: 120 citing papers, 1.9% of this breakdown
0%22.9%Other 32.7%

Fields

  • Environmental Science53.5%
  • Engineering16%
  • Computer Science14.4%
  • Agricultural and Biological Sciences2.5%
  • Earth and Planetary Sciences2.4%
  • Medicine2.3%
  • Other8.9%

Topics

  • Landslides and related hazards9.2%
  • Flood Risk Assessment and Management7.7%
  • Fire effects on ecosystems3.2%
  • Remote Sensing in Agriculture2.9%
  • Hydrology and Watershed Management Studies2.4%
  • Soil Geostatistics and Mapping2.4%
  • Other72.2%

Coauthors

All papers

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  1. Machine learning methods for landslide susceptibility studies: A comparative overview of algorithm performance

    Authors: , , , , , , , - Earth-Science Reviews 2020 cited by 1,130

  2. A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape

    Authors: , , , - Ecological Indicators 2015 cited by 813

  3. Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan

    Authors: , , , , , , , , - Landslides 2019 cited by 519

  4. 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

    Authors: , , , , - Landslides 2015 cited by 1,254

  5. Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan

    Authors: , , , , , , , , , - The Science of The Total Environment 2019 cited by 600

  6. Comparing the prediction performance of a Deep Learning Neural Network model with conventional machine learning models in landslide susceptibility assessment

    Authors: , , , , - CATENA 2020 cited by 465

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

    Authors: , , , , , , , - CATENA 2016 cited by 920

  8. A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran

    Authors: , , , , , , , - The Science of The Total Environment 2018 cited by 761

  9. A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area

    Authors: , , , , , , , - The Science of The Total Environment 2019 cited by 394

  10. Remote Sensing Approaches for Monitoring Mangrove Species, Structure, and Biomass: Opportunities and Challenges

    Authors: , , , , - Remote Sensing, Remote. Sens. 2019 cited by 319

  11. A novel hybrid artificial intelligence approach for flood susceptibility assessment

    Authors: , , , , , , - Environmental Modelling & Software, Environ. Model. Softw. 2017 cited by 638

  12. Hybrid integration of Multilayer Perceptron Neural Networks and machine learning ensembles for landslide susceptibility assessment at Himalayan area (India) using GIS

    Authors: , , , - CATENA 2016 cited by 631

  13. Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm

    Authors: , , , , , - Computer-Aided Civil and Infrastructure Engineering, Comput. Aided Civ. Infrastructure Eng. 2022 cited by 69

  14. Soil Salinity Mapping Using SAR Sentinel-1 Data and Advanced Machine Learning Algorithms: A Case Study at Ben Tre Province of the Mekong River Delta (Vietnam)

    Authors: , , , , , , - Remote Sensing, Remote. Sens. 2019 cited by 163

  15. A novel hybrid approach based on a swarm intelligence optimized extreme learning machine for flash flood susceptibility mapping

    Authors: , , , , , , - CATENA 2019 cited by 310

  16. Optimization of state-of-the-art fuzzy-metaheuristic ANFIS-based machine learning models for flood susceptibility prediction mapping in the Middle Ganga Plain, India

    Authors: , , , , , , , - The Science of The Total Environment 2020 cited by 211

  17. Swarm intelligence optimization of the group method of data handling using the cuckoo search and whale optimization algorithms to model and predict landslides

    Authors: , , , , , , , , - Applied Soft Computing, Appl. Soft Comput. 2021 cited by 87

  18. Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran

    Authors: , , , , , , - Journal of Hydrology 2020 cited by 206

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

    Authors: , , , - Mathematical Problems in Engineering 2012 cited by 573

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

    Authors: , , , , , , , , - CATENA 2018 cited by 505

  21. 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

    Authors: , , , , , - Agricultural and Forest Meteorology 2016 cited by 389

  22. Image Processing-Based Classification of Asphalt Pavement Cracks Using Support Vector Machine Optimized by Artificial Bee Colony

    Authors: , , - Journal of Computing in Civil Engineering, J. Comput. Civ. Eng. 2018 cited by 140

  23. Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran)

    Authors: , , , , , , - Remote Sensing, Remote. Sens. 2018 cited by 270

  24. GIS-based spatial prediction of tropical forest fire danger using a new hybrid machine learning method

    Authors: , , - Ecological Informatics, Ecol. Informatics 2018 cited by 106