Prediction of the landslide susceptibility: Which algorithm, which precision?

By Hamid Reza Pourghasemi, Omid Rahmati. 2018

463 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Management, Monitoring, Policy and Law, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/8140a7ac63f75961e1f79316e011d5dd6f7e89d4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

1. Jakob Richter
2. Alexander Brenning
3. Eugenia Iturritxa
4. Patrick Schratz
5. Jannes Muenchow

In Management, Monitoring, Policy and Law

1. Jakob Richter
2. Eugenia Iturritxa
3. Patrick Schratz
4. Jannes Muenchow
5. Alexander Brenning
6. D. Tien Bui

In Mechanical Engineering

1. Jakob Richter
2. Alexander Brenning
3. Eugenia Iturritxa
4. Patrick Schratz
5. Jannes Muenchow

Citations in the corpus

• Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data (2018, methodology): “…estimation has been emphasized repeatedly in recent years (Gei et al., 2017; Meyer et al., 2018; Wenger & Olden, 2012), such techniques have not been adopted in all cases (Bui et al., 2015; Pourghasemi & Rahmati, 2018; Smoli´nski & Radtke, 2016; Wollan et al., 2008; Youssef et al., 2015).”