Zobrazeno 1 - 10
of 106
pro vyhledávání: '"Danijel Schorlemmer"'
Autor:
José A. Bayona, William H. Savran, Pablo Iturrieta, Matthew C. Gerstenberger, Kenny M. Graham, Warner Marzocchi, Danijel Schorlemmer, Maximilian J. Werner
Publikováno v:
The Seismic Record, Vol 3, Iss 2, Pp 86-95 (2023)
Earthquake forecasting models express hypotheses about seismogenesis that underpin global and regional probabilistic seismic hazard assessments (PSHAs). An implicit assumption is that the comparatively higher spatiotemporal resolution datasets from w
Externí odkaz:
https://doaj.org/article/d6bbc34c50c743499f5cb82517105898
Publikováno v:
ISPRS International Journal of Geo-Information, Vol 12, Iss 4, p 143 (2023)
Natural hazards threaten millions of people all over the world. To address this risk, exposure and vulnerability models with high resolution data are essential. However, in many areas of the world, exposure models are rather coarse and are aggregated
Externí odkaz:
https://doaj.org/article/1ea006c0a4db4eae9f8f0f43097b3e62
Publikováno v:
Annals of Geophysics, Vol 54, Iss 1, Pp 59-65 (2011)
QuakeML is an XML-based data exchange standard for seismology that is in its fourth year of active community-driven development. Its development was motivated by the need to consolidate existing data formats for applications in statistical seismology
Externí odkaz:
https://doaj.org/article/9fe14264d7424f59b4201bfa8806c1a6
Autor:
Massimiliano Stucchi, Francesco Mele, Andrea Rovida, Annemarie Christophersen, Danijel Schorlemmer, Warner Marzocchi
Publikováno v:
Annals of Geophysics, Vol 53, Iss 3, Pp 1-9 (2010)
We describe here the setting up of the first earthquake forecasting experiment for Italy within the Collaboratory for the Study of Earthquake Predictability (CSEP). The CSEP conducts rigorous and actual prospective forecast experiments for different
Externí odkaz:
https://doaj.org/article/3ea079e1aece4983a1c3b755437d3c60
Publikováno v:
Annals of Geophysics, Vol 53, Iss 3, Pp 63-75 (2010)
The Asperity Likelihood Model (ALM) hypothesizes that small-scale spatial variations in the b-value of the Gutenberg-Richter relationship have a central role in forecasting future seismicity. The physical basis of the ALM is the concept that the loca
Externí odkaz:
https://doaj.org/article/851b521dd4674f0abe6c8ccf91822433
Publikováno v:
Annals of Geophysics, Vol 53, Iss 3 (2010)
«A hypothesis that cannot in principle be put to the test of evidence may be interesting, but it is not scientifically useful.» [AAAS 1989]This statement was reported by the American Association for the Advancement of Science – the largest genera
Externí odkaz:
https://doaj.org/article/3405524fafa94e38843194f456ebd1fb
Autor:
Laurens Jozef Nicolaas Oostwegel, Nicolas Garcia Ospina, Tara Evaz Zadeh, Simantini Shinde, Danijel Schorlemmer
Publikováno v:
Abstracts
OpenStreetMap (OSM) is the largest crowd-sourced mapping effort to date, with an infrastructure network that is considered near-complete. The mapping activities started as any crowd-sourced information platform: the community expanded OSM anywhere th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::12db5d8bcf7a7c4053ecfc4d8eb87d5a
https://doi.org/10.5194/egusphere-egu23-13160
https://doi.org/10.5194/egusphere-egu23-13160
Publikováno v:
eISSN
Aftershock forecast models are usually provided on a uniform spatial grid, and the receiver operating characteristic (ROC) curve is often employed for evaluation, drawing a binary comparison of earthquake occurrences or non-occurrence for each grid c
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::677bc509c93c1fac7b4a6ae30c141dc3
https://doi.org/10.5194/egusphere-2023-309
https://doi.org/10.5194/egusphere-2023-309
Assessing or forecasting seismic damage to buildings is an essential issue for earthquake disaster management. In this study, we explore the efficacy of several machine learning models for damage characterization, trained and tested on the database o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f177e1012323172d215e4ac253ae7f70
https://doi.org/10.5194/nhess-2023-7
https://doi.org/10.5194/nhess-2023-7