Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Luísa Vieira Lucchese"'
Publikováno v:
Natural Hazards. 106:2381-2405
Two Artificial Intelligence (AI) methods, Fuzzy Inference System (FIS) and Artificial Neural Network (ANN), are applied to Landslide Susceptibility Mapping (LSM), to compare complementary aspects of the potentials of the two methods and to extract ph
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::992766c1cbdfe237deeb439e6d03374d
https://doi.org/10.1007/s11069-021-04547-6
https://doi.org/10.1007/s11069-021-04547-6
Autor:
Luísa Vieira Lucchese, Guilherme Garcia de Oliveira, Alexander Brenning, Olavo Correa Pedrollo
Landslide Susceptibility Mapping (LSM) and rainfall thresholds are well-documented tools used to model the occurrence of rainfall-induced landslides. In the case of locations where only rainfall can be considered a main landslide trigger, both method
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::13e8f3db85dd6da67827d63a47c1d4ef
https://doi.org/10.5194/egusphere-egu22-4250
https://doi.org/10.5194/egusphere-egu22-4250
Publikováno v:
Journal of Hydraulic Research. 58:725-737
Shallow water models are commonly used to simulate dam-break flow; however, shallow water equations usually assume a hydrostatic pressure assumption that can limit model applications. Dam-break flo...
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2cc9c5481266e5c58ca351809391d5d
https://doi.org/10.1080/00221686.2019.1671509
https://doi.org/10.1080/00221686.2019.1671509
Rainfall-induced landslides have caused destruction and deaths in South America. Accessing its triggers can help researchers and policymakers to understand the nature of the events and to develop more effective warning systems. In this research, trig
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a2e6f5f4f688e29c6a78eadcd003783
https://doi.org/10.5194/egusphere-egu21-1623
https://doi.org/10.5194/egusphere-egu21-1623
Publikováno v:
Environmental monitoring and assessment. 192(2)
Landslide susceptibility maps can be developed with artificial neural networks (ANNs). In order to train our ANNs, a digital elevation model (DEM) and a scar map of one previous event were used. Eleven attributes are generated, possibly containing re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a2f1c8d3fa9fc76bc85700880d53224
https://pubmed.ncbi.nlm.nih.gov/31965339
https://pubmed.ncbi.nlm.nih.gov/31965339
Publikováno v:
CATENA. 198:105067
Landslide susceptibility assessment using Artificial Neural Networks (ANNs) requires occurrence (landslide) and nonoccurrence (not prone to landslide) samples for ANN training. We present empirical evidence that a priori intervention on the nonoccurr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f3e8228f827e20c140cae3d4f3900068
https://doi.org/10.1016/j.catena.2020.105067
https://doi.org/10.1016/j.catena.2020.105067
Autor:
Luísa Vieira Lucchese, Edith Beatriz Camaño Schettini, Leonardo Romero Monteiro, Jorge Hugo Silvestrini
Publikováno v:
Computers & Geosciences. 133:104306
It is well-known that deposits of turbidity currents can significantly change bathymetry. The deposit of a current can alter sedimentation that happens afterwards, changing the deposit shape of a turbidity current. Direct Numerical Simulations of tri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8cb8df16d5d9da169c613f3913fe73a8
https://doi.org/10.1016/j.cageo.2019.104306
https://doi.org/10.1016/j.cageo.2019.104306
Publikováno v:
Revista de Gestão de Água da América Latina. 10:65-75
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9cfe3bcd51f84343ca7b51b8a5ffd05f
https://doi.org/10.21168/rega.v10n2.p65-75
https://doi.org/10.21168/rega.v10n2.p65-75