Baharin bin Ahmad

Global and Planetary Change · 2012–2020

A researcher in the Science corpus: 10 papers; trusts 18 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Baharin bin Ahmad trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

  1. Biswajeet Pradhan
  2. Saro Lee
  3. Isik Yilmaz
  4. Alexander Brenning
  5. D. Tien Bui
  6. Andreas Karlsson
  7. Candan Gokceoglu

Who trusts Baharin bin Ahmad overall

  1. Himan Shahabi
  2. Ataollah Shirzadi

Papers from Baharin bin Ahmad's perspective

Ordered by how strongly the researchers Baharin bin Ahmad trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela
  2. Digital terrain modelling: A review of hydrological, geomorphological, and biological applications
  3. Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran (Proceedings of the Indian Academy of Sciences, Earth and Planetary Sciences)
  4. Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China. (Science of the Total Environment)
  5. Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling (Environmental Modelling & Software)
  6. Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy
  7. Landslide susceptibility mapping : A comparison of logistic regression and neural networks methods in a medium scale study, Hendek Region (Turkey)
  8. Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances (Natural Hazards)
  9. Artificial Neural Networks applied to landslide susceptibility assessment
  10. Determination and application of the weights for landslide susceptibility mapping using an artificial neural network

Their papers