A Nonergodic Ground-Motion Model for the San Francisco Bay Area for Small-Magnitude Earthquakes

Дата публикации: 21-08-2026 00:00:00

ABSTRACT Recently, generative models have become a computationally efficient alternative to physics-based numerical simulations of ground motions. Neural networks can learn from existing ground-motion data to generate unobserved ground-motion data at new source and site locations. A key challenge with generative models is ensuring that predicted ground motions remain within a physically realistic range. For this purpose, we developed an empirical, nonergodic ground-motion model (GMM) for small-magnitude earthquakes in the San Francisco Bay area based on about 5000 recordings per component for Mw ≤ 4 earthquakes. The nonergodic GMM predicts spatially varying median source, site, and path effects for both the Fourier amplitude spectrum (FAS) and the Fourier phase derivative (a proxy for duration), as well as the corresponding epistemic uncertainty for each term. For FAS, our model shows above-average source and site effects in the western part of the region and below-average effects...

Схожие новости

#	Наименование новости	Тональность	Информативность	Дата публикации
1	Best Romantic Movies on Netflix You’ll Fall in Love With	0	0	21-01-2020
2	VfL Bochum: Dieter Hecking verkündet Torwart-Entscheidung	0	0	20-02-2025
3	✨В 2025 году Россия отмечает 80-летие Победы Советского народа над ...	0	0	19-02-2025
4	Белая Холуница: Вечер 24 авг, Сб	0	0	24-08-2019
5	La Escuela Superior de Hostelería de Extremadura reabre su aula restaurante al público un día	0	0	19-02-2025
6	The Role of Digital Strategy Consulting in Business Growth	0	0	20-02-2025
7	Soldi e soldati: la Ue divisa su Kiev dà purtroppo ragione a Trump	0	0	17-02-2025
8	Генассамблея ООН приняла антироссийскую резолюцию по Украине - Лента новостей Курска	0	0	24-02-2025
9	Рязанцы примут участие в полуфинале Всероссийского конкурса общества «Знание»	0	0	10-03-2023
10	Почувствуйте каждый момент Тур де Франс с RadioQ!	0	0	01-07-2024

Классификация: Наука. Схожих патентов: 0. Схожих новостей: 10. Тональность: 0. Информативность: 11.9. Источник: escholarship.org.