Ditapis dengan
Scaling Law Analysis and Aftershock Spatiotemporal Evolution of the Three Str…
The observed scaling properties in the three aftershock sequences of the recent strong earthquakes of magnitudes Mw 6.1, Mw 6.4 and Mw 6.7, which occurred in the Ionian island region on the 26 January 2014 (onshore Cephalonia Island), 17 November 2015 (Lefkada Island) and 25 October 2018 (offshore Zakynthos Island), respectively, are presented. In the analysis, the frequency–magnitude distrib…
- Edisi
- Vol.15, Issue 3, March 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 26 hlm PDF, 2.711 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
Tectonic Setting and Spatiotemporal Earthquake Distribution in Northern Nubia…
The spatiotemporal distribution of major earthquakes in the study area (1600–2024) is analyzed to tentatively recognize the possible connections with the short-term (from decades to centuries) evolution of the ongoing tectonic processes. This study suggests that during the period considered, seismic activity has been predominantly related to the shortening processes accommodating the converge…
- Edisi
- Vol.15, Issue 2, February 2025
- ISBN/ISSN
- 2076-3263
- Deskripsi Fisik
- 15 hlm PDF, 2.127 KB
- Judul Seri
- Geosciences
- No. Panggil
- 550
The role of artificial intelligence and IoT in prediction of earthquakes: Review
Earthquakes are classified as one of the most devastating natural disasters that can have catastrophic effects on the environment, lives, and properties. There has been an increasing interest in the prediction of earthquakes and in gaining a comprehensive understanding of the mechanisms that underlie their generation, yet earthquakes are the least predictable natural disaster. Satellite data, g…
- Edisi
- Vol.5, December 2024
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 19 hlm PDF, 5.965 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
Enhanced crustal and intermediate seismicity in the Hindu Kush-Pamir region r…
The Hindu Kush-Pamir region (HKPR) is characterized by complex ongoing deformation, unique slab geometry, and intermediate seismic activity. The availability of extensive seismological data in recent decades has prompted the use of deep learning algorithms to extract valuable insights. In this study, we present a fully automated approach for augmenting earthquake catalogue within the HKPR. Our …
- Edisi
- Vol.4, December 2023
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 14 hlm PDF, 15.177 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
MLReal: Bridging the gap between training on synthetic data and real data app…
Among the biggest challenges we face in utilizing neural networks trained on waveform (i.e., seismic, electromagnetic, or ultrasound) data is its application to real data. The requirement for accurate labels often forces us to train our networks using synthetic data, where labels are readily available. However, synthetic data often fail to capture the reality of the field/real experiment, and w…
- Edisi
- Vol.3, December 2022
- ISBN/ISSN
- 2666-5441
- Deskripsi Fisik
- 14 hlm PDF, 3.698 KB
- Judul Seri
- Artificial Intelligence in Geosciences
- No. Panggil
- 551
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