A Novel Ensemble Artificial Intelligence Approach for Gully Erosion Mapping in a Semi-Arid Watershed (Iran)

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ID: 261635
2019
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Abstract
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, …
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d2019sensorsa Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Tien Bui D;Shirzadi A;Shahabi H;Chapi K;Omidavr E;Pham BT;Talebpour Asl D;Khaledian H;Pradhan B;Panahi M;Bin Ahmad B;Rahmani H;Gróf G;Lee S;;
Journal sensors
Year 2019
DOI
DOI not found
URL
https://www.ncbi.nlm.nih.gov/pubmed/31146336
Keywords
National Center for Biotechnology Information NCBI NLM MEDLINE pubmed abstract nih national institutes of health national library of medicine ataollah shirzadi dieu tien bui pmid:31146336 pmc6603737 doi:10.3390/s19112444 saro lee Machine learning gully erosion ensemble algorithms geomorphology geographic information science kurdistan province

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