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

Dou, Jie, Yunus, Ali P, Dieu, Tien Bui et al. (2019). Assessment of advanced random forest and decision tree algorithms for modeling rainfall-induced landslide susceptibility in the Izu-Oshima Volcanic Island, Japan . Science of the Total Environment, 662 332-346. 10.1016/j.scitotenv.2019.01.221

ESI Most Cited Paper International Collaboration

cited authors

  • Dou, Jie; Yunus, Ali P; Dieu, Tien Bui; Merghadi, Abdelaziz; Sahana, Mehebub; Zhu, Zhongfan; Chen, Chi-Wen; Khosravi, Khabat; Yang, Yong; Binh, Thai Pham

sustainable development goals

authors

publication date

  • April 20, 2019

published in

keywords

  • AREA
  • Decision tree
  • ENTROPY
  • Environmental Sciences
  • Environmental Sciences & Ecology
  • FUZZY
  • INTEGRATION
  • Izu-Oshima Volcano Island
  • LOGISTIC-REGRESSION
  • Life Sciences & Biomedicine
  • Machine learning
  • Rainfall-induced landslide
  • Random forest
  • SHALLOW
  • SPATIAL PREDICTION
  • SUPPORT VECTOR MACHINE
  • Science & Technology
  • Susceptibility
  • TRIGGERED LANDSLIDES
  • WEIGHTS-OF-EVIDENCE

Digital Object Identifier (DOI)

start page

  • 332

end page

  • 346

volume

  • 662