登录注册
Quick Links : Mindat手册The Rock H. Currier Digital LibraryMindat Newsletter [Free Download]
主页关于 MindatMindat手册Mindat的历史版权Who We Are联系我们于 Mindat.org刊登广告
捐赠给 MindatCorporate Sponsorship赞助板页已赞助的板页在 Mindat刊登 广告的广告商于 Mindat.org刊登广告
Learning CenterWhat is a mineral?The most common minerals on earthInformation for EducatorsMindat ArticlesThe ElementsThe Rock H. Currier Digital LibraryGeologic Time
搜索矿物的性质搜索矿物的化学Mineral Visual ExplorerAdvanced Locality Search随意显示任何一 种矿物Random Locality使用minID搜索邻近产地Search Articles搜索词汇表更多搜索选项
搜索:
矿物名称:
地区产地名称:
关键字:
 
Mindat手册添加新照片Rate Photos产区编辑报告Coordinate Completion Report添加词汇表项目
Mining Companies统计会员列表Mineral MuseumsClubs & Organizations矿物展及活动The Mindat目录表设备设置The Mineral QuizTime Machine
照片搜索Photo GalleriesSearch by ColorPhoto Colour Explorer今天最新的照片昨天最新的照片用户照片相集过去每日精选照片相集Photography

Arabameri, Alireza, Cerda, Artemi, Tiefenbacher, John P. (2019) Spatial Pattern Analysis and Prediction of Gully Erosion Using Novel Hybrid Model of Entropy-Weight of Evidence. Water, 11 (6) 1129pp. doi:10.3390/w11061129

Advanced
   -   Only viewable:
Reference TypeJournal (article/letter/editorial)
TitleSpatial Pattern Analysis and Prediction of Gully Erosion Using Novel Hybrid Model of Entropy-Weight of Evidence
JournalWater
AuthorsArabameri, AlirezaAuthor
Cerda, ArtemiAuthor
Tiefenbacher, John P.Author
Year2019 (May 29)Volume11
Issue6
PublisherMDPI AG
DOIdoi:10.3390/w11061129Search in ResearchGate
Generate Citation Formats
Mindat Ref. ID12876102Long-form Identifiermindat:1:5:12876102:3
GUID0
Full ReferenceArabameri, Alireza, Cerda, Artemi, Tiefenbacher, John P. (2019) Spatial Pattern Analysis and Prediction of Gully Erosion Using Novel Hybrid Model of Entropy-Weight of Evidence. Water, 11 (6) 1129pp. doi:10.3390/w11061129
Plain TextArabameri, Alireza, Cerda, Artemi, Tiefenbacher, John P. (2019) Spatial Pattern Analysis and Prediction of Gully Erosion Using Novel Hybrid Model of Entropy-Weight of Evidence. Water, 11 (6) 1129pp. doi:10.3390/w11061129
In(2019, May) Water Vol. 11 (6) MDPI AG

See Also

These are possibly similar items as determined by title/reference text matching only.

Arabameri, Alireza, Cerda, Artemi, Pradhan, Biswajeet, Tiefenbacher, John P., Lombardo, Luigi, Bui, Dieu Tien (2020) A methodological comparison of head-cut based gully erosion susceptibility models: Combined use of statistical and artificial intelligence. Geomorphology, 359. 107136 doi:10.1016/j.geomorph.2020.107136
Arabameri, Alireza, Tiefenbacher, John P., Blaschke, Thomas, Pradhan, Biswajeet, Tien Bui, Dieu (2020) Morphometric Analysis for Soil Erosion Susceptibility Mapping Using Novel GIS-Based Ensemble Model. Remote Sensing, 12 (5). doi:10.3390/rs12050874
Arabameri, Alireza, Asadi Nalivan, Omid, Saha, Sunil, Roy, Jagabandhu, Pradhan, Biswajeet, Tiefenbacher, John P., Thi Ngo, Phuong Thao (2020) Novel Ensemble Approaches of Machine Learning Techniques in Modeling the Gully Erosion Susceptibility. Remote Sensing, 12 (11). doi:10.3390/rs12111890
Arabameri, Alireza, Chen, Wei, Blaschke, Thomas, Tiefenbacher, John P., Pradhan, Biswajeet, Tien Bui, Dieu (2019) Gully Head-Cut Distribution Modeling Using Machine Learning Methods—A Case Study of N.W. Iran. Water, 12 (1) 16pp. doi:10.3390/w12010016
Chen, Xiaohui; Arabameri, Alireza; Santosh, M.; Naqvi, Hasan Raja; Ramiz, Mohd (2026) Gully erosion prediction using weight of evidence and advanced machine learning models. Advances in Space Research, 77 (2). doi:10.1016/j.asr.2025.10.047
Arabameri, Alireza, Chen, Wei, Loche, Marco, Zhao, Xia, Li, Yang, Lombardo, Luigi, Cerda, Artemi, Pradhan, Biswajeet, Bui, Dieu Tien (2020) Comparison of machine learning models for gully erosion susceptibility mapping. Geoscience Frontiers, 11 (5) 1609-1620 doi:10.1016/j.gsf.2019.11.009
Arabameri, Alireza, Pradhan, Biswajeet, Rezaei, Khalil (2019) Spatial prediction of gully erosion using ALOS PALSAR data and ensemble bivariate and data mining models. Geosciences Journal, 23. 669-686 doi:10.1007/s12303-018-0067-3
Arabameri, , Cerda, , Rodrigo-Comino, , Pradhan, , Sohrabi, , Blaschke, , Tien Bui, (2019) Proposing a Novel Predictive Technique for Gully Erosion Susceptibility Mapping in Arid and Semi-arid Regions (Iran). Remote Sensing, 11 (21). doi:10.3390/rs11212577
Arabameri, Alireza, Santosh, M., Moayedi, Hossein, Tiefenbacher, John P., Pal, Subodh Chandra, Nalivan, Omid Asadi, Costache, Romulus, Ahmed, Naser, Hoque, Muhammad Al-Amin, Chakrabortty, Rabin, Cerda, Artemi (2022) Application of the novel state-of-the-art soft computing techniques for groundwater potential assessment. Arabian Journal of Geosciences, 15 (10) doi:10.1007/s12517-021-09005-y
Arabameri, Alireza, Rezaie, Fatemeh, Pal, Subodh Chandra, Cerda, Artemi, Saha, Asish, Chakrabortty, Rabin, Lee, Saro (2021) Modelling of piping collapses and gully headcut landforms: Evaluating topographic variables from different types of DEM. Geoscience Frontiers, 12 (6) 101230pp. doi:10.1016/j.gsf.2021.101230
Arabameri, Alireza, Pradhan, Biswajeet, Pourghasemi, Hamid Reza, Rezaei, Khalil, Kerle, Norman (2018) Spatial Modelling of Gully Erosion Using GIS and R Programing: A Comparison among Three Data Mining Algorithms. Applied Sciences, 8. 1369pp. doi:10.3390/app8081369
 
and/or  
版权所有© mindat.org1993年至2026年，除了规定的地方。 Mindat.org全赖于全球数千个以上成员和支持者们的参与。
To cite: Ralph, J., Von Bargen, D., Martynov, P., Zhang, J., Que, X., Prabhu, A., Morrison, S. M., Li, W., Chen, W., & Ma, X. (2025). Mindat.org: The open access mineralogy database to accelerate data-intensive geoscience research. American Mineralogist, 110(6), 833–844. doi:10.2138/am-2024-9486.
隐私政策 - 条款和条款细则 - 联络我们 - Report a bug/vulnerability Current server date and time: 2026.6.6 02:46:18
Go to top of page