A Novel Ensemble Artificial Intelligence Approach for Gully Erosion Mapping in a Semi-Arid Watershed (Iran)
In this study, we introduced a novel hybrid artificial intelligence approach of rotation forest (RF) as a Meta/ensemble classifier based on alternating decision tree (ADTree) as a base classifier called RF-ADTree in order to spatially predict gully erosion at Klocheh watershed of Kurdistan province,...
Main Authors: | Dieu Tien Bui, Ataollah Shirzadi, Himan Shahabi, Kamran Chapi, Ebrahim Omidavr, Binh Thai Pham, Dawood Talebpour Asl, Hossein Khaledian, Biswajeet Pradhan, Mahdi Panahi, Baharin Bin Ahmad, Hosein Rahmani, Gyula Gróf, Saro Lee |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-05-01
|
Series: | Sensors |
Subjects: | |
Online Access: | https://www.mdpi.com/1424-8220/19/11/2444 |
Similar Items
-
A novel ensemble artificial intelligence approach for gully erosion mapping in a semi-arid watershed (Iran)
by: Dieu, Tien Bui, et al.
Published: (2019) -
GIS-Based Gully Erosion Susceptibility Mapping: A Comparison of Computational Ensemble Data Mining Models
by: Viet-Ha Nhu, et al.
Published: (2020-03-01) -
GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran
by: Xinxiang Lei, et al.
Published: (2020-08-01) -
Robustness analysis of machine learning classifiers in predicting spatial gully erosion susceptibility with altered training samples
by: Tusar Kanti Hembram, et al.
Published: (2021-01-01) -
DEVELOPMENT OF THE ROAD GULLY IN GORZKÓW (LUBLIN UPLAND)
by: Andrzej Mazur, et al.
Published: (2015-10-01)