Filippo Catani
Management, Monitoring, Policy and Law · 2005–2018
A researcher in the Science corpus: 4 papers; trusts 7 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Management, Monitoring, Policy and Law — 19 citations into it; #574 of 2,821 by trust here, #425 by citations
- Global and Planetary Change — 10 citations into it; #6,745 of 10,225 by trust here, #6,266 by citations
- Safety, Risk, Reliability and Quality — 10 citations into it; #822 of 1,220 by trust here, #269 by citations
- Mechanical Engineering — 9 citations into it
- Artificial Intelligence — 5 citations into it
Whom Filippo Catani trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Mahesh Pal
- C. Baeza
- Bakhtiar Feizizadeh
- Biswajeet Pradhan
- David W. Hosmer Jr.
- Saro Lee
- Trevor J. Hastie
- Jisoo Ham
- Fausto Guzzetti
- Thomas Blaschke
Who trusts Filippo Catani overall
- Biswajeet Pradhan
- Binh Thai Pham
- D. Tien Bui
- Bahareh Kalantar
- Indra Prakash
- Saro Lee
- Zhu Lei
- Khabat Khosravi
- Qiqing Wang
- Mathieu Marmion
Papers from Filippo Catani's perspective
Ordered by how strongly the researchers Filippo Catani trusts endorse each paper. Same corpus, a different order for every researcher.
- Random Forests
- The Nature of Statistical Learning Theory
- 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 assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling (Environmental Modelling & Software)
- Artificial Neural Networks applied to landslide susceptibility assessment
- Applied Logistic Regression: Hosmer/Applied Logistic Regression
- Techniques for evaluating the performance of landslide susceptibility models
- 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)
- Validation and Evaluation of Predictive Models in Hazard Assessment and Risk Management
Their papers
- Landslide susceptibility modeling applying machine learning methods: A case study from Longju in the Three Gorges Reservoir area, China (2018) — 351 citations
- Quantitative comparison between two different methodologies to define rainfall thresholds for landslide forecasting (2015) — 73 citations
- Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues (2013) — 633 citations
- Artificial Neural Networks applied to landslide susceptibility assessment (2005) — 556 citations