Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Samuel Roeslin"'
Publikováno v:
Frontiers in Built Environment, Vol 4 (2018)
Understanding seismic risk enables efficient resource allocation in the effort to increase the resilience of our cities and communities. Field reconnaissance and data collection following disasters document the damaging effects of earthquakes to enab
Externí odkaz:
https://doaj.org/article/fc47dabf2d9d4fdba5a1de3e51601500
Autor:
Samuel Roeslin
The 2010-2011 Canterbury Earthquake sequence (CES) led to unprecedented building damage in the Canterbury region, New Zealand. Commercial and residential buildings were significantly affected. Due to New Zealand’s unique insurance setting, around 8
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a0b8d67903cd3429e7e9c251290d0ebc
https://doi.org/10.5194/egusphere-egu23-2996
https://doi.org/10.5194/egusphere-egu23-2996
This paper presents a new framework for the seismic loss prediction of residential buildings in Ōtautahi / Christchurch, New Zealand. It employs data science techniques, geospatial tools, and machine learning (ML) trained on insurance claims data fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8bcff441fd6d55b1974d263962bb99bb
https://nhess.copernicus.org/articles/23/1207/2023/
https://nhess.copernicus.org/articles/23/1207/2023/
This paper presents a new framework for the seismic loss prediction of residential buildings in Christchurch, New Zealand. It employs data science techniques, geospatial tools, and machine learning (ML) trained on insurance claims data from the Earth
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::760bc2a75985d3afed4f3504b9a2743c
https://nhess.copernicus.org/preprints/nhess-2022-227/
https://nhess.copernicus.org/preprints/nhess-2022-227/
Autor:
Quincy Ma, Joerg Wicker, Liam Wotherspoon, Alonso Gómez-Bernal, Samuel Roeslin, Hugon Juárez-Garcia
Publikováno v:
Earthquake Spectra. 36:314-339
The 2017 Puebla, Mexico, earthquake event led to significant damage in many buildings in Mexico City. In the months following the earthquake, civil engineering students conducted detailed building assessments throughout the city. They collected build
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030438869
PKDD/ECML Workshops (2)
PKDD/ECML Workshops (2)
In 2010–2011, New Zealand experienced the most damaging earthquakes in its history. It led to extensive damage to Christchurch buildings, infrastructure and its surroundings; affecting commercial and residential buildings. The direct economic losse
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8a717e4fbb2d7c25cdb570977f6dc0d4
https://doi.org/10.1007/978-3-030-43887-6_8
https://doi.org/10.1007/978-3-030-43887-6_8
Publikováno v:
Frontiers in Built Environment, Vol 4 (2018)
Understanding seismic risk enables efficient resource allocation in the effort to increase the resilience of our cities and communities. Field reconnaissance and data collection following disasters document the damaging effects of earthquakes to enab
Publikováno v:
Journal of Building Engineering. 35:102022
In recent years, the system known as diagrid (diagonal grid) has been used in several tall buildings around the world. Despite the large advantages that the innovative structural system represents in terms of sustainability, its use has not been suff