Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Neural Network-Based Subduction Ground Motion Model and Its Application to New Zealand and the Andaman and Nicobar Islands
A deep learning model is developed for the Next Generation Attenuation – Subduction database for predicting spectral accelerations and peak amplitude measures. The developed model satisfies the statistical criteria necessary for prediction. Standard deviations lie in 0.2864–0.3809, 0–0.2696, and 0.4514–0.7892, range for inter-event, -region, and intra-events, respectively. Transfer learning is applied to the New Zealand region. Probabilistic seismic hazard analysis is performed for the Andaman-Nicobar region and obtained a peak ground acceleration of 0.6–0.7 g and 0.4–0.5 g at the Andaman and the Nicobar Islands, respectively, for a 2475-year return period.
Neural Network-Based Subduction Ground Motion Model and Its Application to New Zealand and the Andaman and Nicobar Islands
A deep learning model is developed for the Next Generation Attenuation – Subduction database for predicting spectral accelerations and peak amplitude measures. The developed model satisfies the statistical criteria necessary for prediction. Standard deviations lie in 0.2864–0.3809, 0–0.2696, and 0.4514–0.7892, range for inter-event, -region, and intra-events, respectively. Transfer learning is applied to the New Zealand region. Probabilistic seismic hazard analysis is performed for the Andaman-Nicobar region and obtained a peak ground acceleration of 0.6–0.7 g and 0.4–0.5 g at the Andaman and the Nicobar Islands, respectively, for a 2475-year return period.
Neural Network-Based Subduction Ground Motion Model and Its Application to New Zealand and the Andaman and Nicobar Islands
Vemula, Sreenath (Autor:in) / Kp, Sreejaya (Autor:in) / Raghukanth, S.T.G. (Autor:in)
Journal of Earthquake Engineering ; 27 ; 2863-2886
27.07.2023
24 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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