S. M. F. Aghda
Management, Monitoring, Policy and Law · 2013
A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Management, Monitoring, Policy and Law — 13 citations into it; #970 of 2,821 by trust here, #1,264 by citations
- Global and Planetary Change — 10 citations into it; #4,004 of 10,225 by trust here, #5,940 by citations
- Safety, Risk, Reliability and Quality — 8 citations into it
- Mechanical Engineering — 6 citations into it; #3,102 of 8,300 by trust here, #5,119 by citations
Whom S. M. F. Aghda trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts S. M. F. Aghda overall
Papers from S. M. F. Aghda's perspective
Ordered by how strongly the researchers S. M. F. Aghda trusts endorse each paper. Same corpus, a different order for every researcher.
- 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)
- 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)
- An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps
- Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy
- Digital terrain modelling: A review of hydrological, geomorphological, and biological applications
- Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression (Landslides)
- Assessment of Landslide Susceptibility by Decision Trees in the Metropolitan Area of Istanbul, Turkey
- Landslide susceptibility mapping using frequency ratio, logistic regression, artificial neural networks and their comparison: A case study from Kat landslides (Tokat - Turkey) (Computational Geosciences)
- Determination and application of the weights for landslide susceptibility mapping using an artificial neural network
- A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS (Computational Geosciences)