Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms

Năm xuất bản2020

Nguồn học thuậtInternational Journal of Environmental Research and Public Health

Định danhDOI 10.3390/ijerph17082749

TRÍCH DẪN ĐỀ XUẤT

Viet‐Ha Nhu; Ataollah Shirzadi; Himan Shahabi; Sushant K. Singh; Nadhir Al‐Ansari; John J. Clague; Abolfazl Jaafari; Wei Chen; Shaghayegh Miraki; Jie Dou; Chinh Luu; K. Górski; Binh Thai Pham; Huu Duy Nguyen; Baharin Bin Ahmad (2020). Shallow Landslide Susceptibility Mapping: A Comparison between Logistic Model Tree, Logistic Regression, Naïve Bayes Tree, Artificial Neural Network, and Support Vector Machine Algorithms. International Journal of Environmental Research and Public Health, 17(8), 2749. https://doi.org/10.3390/ijerph17082749

Thông tin thư mục

Nguồn/Tạp chí: International Journal of Environmental Research and Public Health
Tập: 17
Số: 8
Trang: 2749
Nhà xuất bản: Multidisciplinary Digital Publishing Institute
DOI: 10.3390/ijerph17082749 ↗

Từ khóa

Logistic model tree; Logistic regression; Landslide; Support vector machine; Decision tree; Machine learning; Artificial neural network; Artificial intelligence; Naive Bayes classifier; Statistics; Computer science; Tree (set theory); Algorithm; Mean squared error; Data mining; Mathematics; Geology; Geomorphology