Soft computing machine learning applications for assessing regional-scale landslide susceptibility in the Nepal Himalaya (Englisch)
- Neue Suche nach: Manandhar, Bikesh
- Weitere Informationen zu Manandhar, Bikesh:
-
https://orcid.org/0000-0002-5806-9727
- Neue Suche nach: Huynh, Thanh-Canh
- Weitere Informationen zu Huynh, Thanh-Canh:
-
https://orcid.org/0000-0002-9231-2129
- Neue Suche nach: Bhattarai, Pawan Kumar
- Weitere Informationen zu Bhattarai, Pawan Kumar:
-
https://orcid.org/0009-0007-3860-3367
- Neue Suche nach: Shrestha, Suchita
- Weitere Informationen zu Shrestha, Suchita:
-
https://orcid.org/0000-0001-7765-7930
- Neue Suche nach: Pradhan, Ananta Man Singh
- Weitere Informationen zu Pradhan, Ananta Man Singh:
-
https://orcid.org/0000-0003-3281-7739
- Neue Suche nach: Manandhar, Bikesh
- Weitere Informationen zu Manandhar, Bikesh:
-
https://orcid.org/0000-0002-5806-9727
- Neue Suche nach: Huynh, Thanh-Canh
- Weitere Informationen zu Huynh, Thanh-Canh:
-
https://orcid.org/0000-0002-9231-2129
- Neue Suche nach: Bhattarai, Pawan Kumar
- Weitere Informationen zu Bhattarai, Pawan Kumar:
-
https://orcid.org/0009-0007-3860-3367
- Neue Suche nach: Shrestha, Suchita
- Weitere Informationen zu Shrestha, Suchita:
-
https://orcid.org/0000-0001-7765-7930
- Neue Suche nach: Pradhan, Ananta Man Singh
- Weitere Informationen zu Pradhan, Ananta Man Singh:
-
https://orcid.org/0000-0003-3281-7739
In:
Engineering Computations
;
41
, 3
;
655-681
;
2024
-
ISSN:
- Aufsatz (Zeitschrift) / Elektronische Ressource
-
Titel:Soft computing machine learning applications for assessing regional-scale landslide susceptibility in the Nepal Himalaya
-
Weitere Titelangaben:Soft computing machine learning applications
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Beteiligte:Manandhar, Bikesh ( Autor:in ) / Huynh, Thanh-Canh ( Autor:in ) / Bhattarai, Pawan Kumar ( Autor:in ) / Shrestha, Suchita ( Autor:in ) / Pradhan, Ananta Man Singh ( Autor:in )
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Erschienen in:Engineering Computations ; 41, 3 ; 655-681
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Verlag:
- Neue Suche nach: Emerald Publishing Limited
-
Erscheinungsdatum:13.05.2024
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Format / Umfang:27 pages
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ISSN:
-
DOI:
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Medientyp:Aufsatz (Zeitschrift)
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Format:Elektronische Ressource
-
Sprache:Englisch
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Schlagwörter:
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Datenquelle:
Inhaltsverzeichnis – Band 41, Ausgabe 3
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