Landslide spatial modeling: Introducing new ensembles of ANN, MaxEnt, and SVM machine learning techniques
By Wei Chen, Hamid Reza Pourghasemi, Aiding Kornejady, Ning Zhang. 2017
365 citations recorded by the source corpus.
Subfields: Civil and Structural Engineering, Management, Monitoring, Policy and Law, Safety, Risk, Reliability and Quality
View Paper: https://www.semanticscholar.org/paper/4b1df1ff656be5293004ee3deddb7c31473a99c9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Civil and Structural Engineering
In Management, Monitoring, Policy and Law
- Binh Thai Pham
- Himan Shahabi
- D. Tien Bui
- Ataollah Shirzadi
- Indra Prakash
- Baharin bin Ahmad
- Wei Chen
- Haoyuan Hong
In Safety, Risk, Reliability and Quality
- Binh Thai Pham
- Indra Prakash
- Haoyuan Hong
- D. Tien Bui
- Wei Chen
- Himan Shahabi
- Ataollah Shirzadi
- Baharin bin Ahmad
Citations in the corpus
- Influence of Data Splitting on Performance of Machine Learning Models in Prediction of Shear Strength of Soil (2021, background): “It can be stated that ANNmodel has been reaffirmed as the best single ML model for solving most of the real-word problems [106, 107].”
- Landslide susceptibility modelling using different advanced decision trees methods (2018, methodology): “…0.5∗Ln W + (D1 > D2) W − (D1 > D2) (4) Where, W indicates the sum of the weights of all labelled samples, the best of D1 and D2 can be calculated by minimising the f (D1, D2) presented as follows (Chen et al. 2017b): f (D1, D2) = 2 W + (D1 > D2)∗W − (D1 > D2) √ + W + (D1 > D2(D1 > D2) √ +W(D2) (5)”
- A novel ensemble approach of bivariate statistical-based logistic model tree classifier for landslide susceptibility assessment (2018, methodology): “…Chen et al. 2017b), decision trees (Pham et al. 2016; Chen et al. 2017h, 2017g), support vector machines (Colkesen et al. 2016; Hong et al. 2016b; Chen et al. 2017c; Shirzadi et al. 2017c), naive Bayes (Pham et al. 2017a; Shirzadi et al. 2017a), random forest (Youssef et al. 2016; Chen et al.…”
- A Survey on ensemble learning under the era of deep learning (2021, methodology): “For the landslide susceptibility mapping, Chen et al. (Chen et al. 2017) proposed several ensembles using multiple base learners that were heterogeneously trained with artificial neural network (ANN) (Rumelhart et al. 1986), maximum entropy (MaxEnt) (Phillips et al. 2004) and SVM (Chang and Lin 2011”