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Sökning: WFRF:(Jaafari Abolfazl) > Novel Ensemble Land...

LIBRIS Formathandbok  (Information om MARC21)
FältnamnIndikatorerMetadata
00005867naa a2200577 4500
001oai:DiVA.org:ltu-79019
003SwePub
008200527s2020 | |||||||||||000 ||eng|
0247 a https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-790192 URI
0247 a https://doi.org/10.3390/app101137102 DOI
040 a (SwePub)ltu
041 a engb eng
042 9 SwePub
072 7a ref2 swepub-contenttype
072 7a art2 swepub-publicationtype
1001 a Tran, Quoc Cuongu Institute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam4 aut
2451 0a Novel Ensemble Landslide Predictive Models Based on the Hyperpipes Algorithm :b A Case Study in the Nam Dam Commune, Vietnam
264 c 2020-05-27
264 1a Switzerland :b MDPI,c 2020
338 a electronic2 rdacarrier
500 a Validerad;2020;Nivå 2;2020-06-15 (alebob)
520 a Development of landslide predictive models with strong prediction power has become a major focus of many researchers. This study describes the first application of the Hyperpipes (HP) algorithm for the development of the five novel ensemble models that combine the HP algorithm and the AdaBoost (AB), Bagging (B), Dagging, Decorate, and Real AdaBoost (RAB) ensemble techniques for mapping the spatial variability of landslide susceptibility in the Nam Dan commune, Ha Giang province, Vietnam. Information on 76 historical landslides and ten geo-environmental factors (slope degree, slope aspect, elevation, topographic wetness index, curvature, weathering crust, geology, river density, fault density, and distance from roads) were used for the construction of the training and validation datasets that are the prerequisites for building and testing the proposed models. Using different performance metrics (i.e., the area under the receiver operating characteristic curve (AUC), negative predictive value, positive predictive value, accuracy, sensitivity, specificity, root mean square error, and Kappa), we verified the proficiency of all five ensemble learning techniques in increasing the fitness and predictive powers of the base HP model. Based on the AUC values derived from the models, the ensemble ABHP model that yielded an AUC value of 0.922 was identified as the most efficient model for mapping the landslide susceptibility in the Nam Dan commune, followed by RABHP (AUC = 0.919), BHP (AUC = 0.909), Dagging-HP (AUC = 0.897), Decorate-HP (AUC = 0.865), and the single HP model (AUC = 0.856), respectively. The novel ensemble models proposed for the Nam Dan commune and the resultant susceptibility maps can aid land-use planners in the development of efficient mitigation strategies in response to destructive landslides.
650 7a TEKNIK OCH TEKNOLOGIERx Samhällsbyggnadsteknikx Geoteknik0 (SwePub)201062 hsv//swe
650 7a ENGINEERING AND TECHNOLOGYx Civil Engineeringx Geotechnical Engineering0 (SwePub)201062 hsv//eng
653 a AdaBoost
653 a Bagging
653 a Dagging
653 a Decorate
653 a Real AdaBoost
653 a ensemble modeling
653 a machine learning
653 a Soil Mechanics
653 a Geoteknik
7001 a Minh, Duc Dou VNU University of Science, Vietnam National University, 334 Nguyen Trai, Hanoi 100000, Vietnam4 aut
7001 a Jaafari, Abolfazlu Research Institute of Forests and Rangelands, Agricultural Research, Education, and Extension Organization (AREEO), P.O. Box 64414-356, Tehran 64414, Iran4 aut
7001 a Al-Ansari, Nadhir,d 1947-u Luleå tekniska universitet,Geoteknologi4 aut0 (Swepub:ltu)nadhir
7001 a Minh, Duc Daou Institute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam. Vietnam Academy of Sciences and Technology, Graduate University of Science and Technology, 18 Hoang Quoc Viet, Hanoi 100000, Vietnam4 aut
7001 a Van, Duc Tungu Institute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam4 aut
7001 a Nguyen, Duc Anhu Institute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam4 aut
7001 a Tran, Trung Hieuu Institute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnam4 aut
7001 a Ho, Lanh Siu Civil and Environmental Engineering Program, Graduate School of Advanced Science and Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, Hiroshima 739-527, Japan4 aut
7001 a Nguyen, Duy Huuu Faculty of Geography, VNU University of Science, Vietnam National University, 334 Nguyen Trai, Hanoi 100000, Vietnam4 aut
7001 a Prakash, Indrau Department of Science & Technology, Bhaskarcharya Institute for Space Applications and Geo-Informatics (BISAG), Government of Gujarat, Gandhinagar 382002, India4 aut
7001 a Le, Hiep Vanu Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam4 aut
7001 a Pham, Binh Thaiu University of Transport Technology, Hanoi 100000, Vietnam4 aut
7102 a Institute of Geological Sciences, Vietnam Academy of Science and Technology, 84 Chua Lang Street, Dong Da, Hanoi 100000, Vietnamb VNU University of Science, Vietnam National University, 334 Nguyen Trai, Hanoi 100000, Vietnam4 org
7730 t Applied Sciencesd Switzerland : MDPIg 10:11q 10:11x 2076-3417
8564 u https://ltu.diva-portal.org/smash/get/diva2:1432470/FULLTEXT01.pdfx primaryx Raw objecty fulltext:print
8564 u https://www.mdpi.com/2076-3417/10/11/3710/pdf
8564 8u https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-79019
8564 8u https://doi.org/10.3390/app10113710

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