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Ditemukan 3 dari pencarian Anda melalui kata kunci: subject="Earthquake early warn...
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Toward earthquake early warning: A convolutional neural network for rapid ear…
Komentar Bagikan
Fanchun MengTao RenZhenxian LiuZhida Zhong

Earthquake early warning (EEW) is one of the important tools to reduce the hazard of earthquakes. In contemporary seismology, EEW is typically transformed into a fast classification of earthquake magnitude, i.e., large magnitude earthquakes that require warning are in the positive category and vice versa in the negative category. However, the current standard information signal processing routi…

Edisi
Vol.4, December 2023
ISBN/ISSN
2666-5441
Deskripsi Fisik
8 hlm PDF, 5.714 KB
Judul Seri
Artificial Intelligence in Geosciences
No. Panggil
551
cover
Developing ground motion prediction models for West Java: A machine learning …
Komentar Bagikan
Andy RachmadanArdiansyah KoeshidayatullahSanLinn I. Kaka

Indonesia, one of the most earthquake-prone countries in the world, is currently developing an Earthquake Early Warning (EEW) system. A key component of this system, the Regional EEW, relies on Ground Motion Prediction models (GMPMs) to issue end-user alerts. However, in West Java, one of the pilot regions for this project, there is a lack of region-specific GMPMs essential for accurate early w…

Edisi
Vol.25, February 2025
ISBN/ISSN
2590-1974
Deskripsi Fisik
14 hlm PDF, 10,819 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
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Deep learning for real-time P-wave detection: A case study in Indonesia’s e…
Komentar Bagikan
Sri WidiyantoroDadan RamdaniAjat SudrajatAdi WibowoLeni Sophia HelianiCecep PratamaDavid Prambudi SaharaMizan Bustanul Fuady BisriSidik Tri WibowoSatriawan Rasyid Purnama

Detecting seismic events in real-time for prompt alerts and responses is a challenging task that requires accurately capturing P-wave arrivals. This task becomes even more challenging in regions like Indonesia, where widely spaced seismic stations exist. The wide station spacing makes associating the seismic signals with specific even more difficult. This paper proposes a novel deep learning-ba…

Edisi
Vol.24, December 2024
ISBN/ISSN
2590-1974
Deskripsi Fisik
16 hlm PDF, 16.531 KB
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136