Zobrazeno 1 - 10
of 78
pro vyhledávání: '"Hao Kuo-Chen"'
Publikováno v:
Journal of Asian Earth Sciences: X, Vol 12, Iss , Pp 100182- (2024)
The Meishan-Chiayi area of western Taiwan has a large probability of producing a major earthquake in the near future. Historically, one of the largest and most damaging of Taiwan’s earthquakes occurred there. It is, therefore, important to have a w
Externí odkaz:
https://doaj.org/article/7f6f80fefa754713b06cdd9912d3f146
Autor:
Wei-Fang Sun, Sheng-Yan Pan, Chun-Ming Huang, Zhuo-Kang Guan, I-Chin Yen, Chun-Wei Ho, Tsung-Chih Chi, Chin-Shang Ku, Bor-Shouh Huang, Ching-Chou Fu, Hao Kuo-Chen
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 35, Iss 1, Pp 1-16 (2024)
Abstract On 18 September 2022, the MW 6.9 Chihshang earthquake struck the south half of the Longitudinal Valley, Taiwan, and caused severe damage. A precise and rapid report for the distribution of aftershock sequence after a devastating earthquake p
Externí odkaz:
https://doaj.org/article/afd8351a16214813bdf7df90874546d7
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 31, Iss 4, Pp 479-486 (2020)
The empirical attenuation functions for Local Magnitude (ML) currently used in Taiwan have been known for overestimated magnitudes around 0.2 compared with moment magnitude (MW) for shallow earthquakes (depths ≤ 35 km). Moreover, for deep earthquak
Externí odkaz:
https://doaj.org/article/9078a69c9dee4c6ca8559a84d13f6b1d
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 30, Iss 3, Pp 337-350 (2019)
A deadly Mw 6.4 earthquake occurred in the Hualien area of eastern Taiwan on 6 February 2018. It caused severe damage to infrastructure and creating surface ruptures in several areas mostly near the Milun Fault in Hualien City. In this study, we inve
Externí odkaz:
https://doaj.org/article/9ddd29896636419bb35e5ebb7f910649
Autor:
Hao Kuo-Chen, Kai-Xun Chen, Wei-Fang Sun, Chun-Wei Ho, Yuan-Hsi Lee, Zhuo-Kang Guan, Chu-Chun Kang, Wen-Yen Chang
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 28, Iss 5, Pp 693-701 (2017)
Mw 6.4 Meinong earthquake occurred on 6 February 2016 in southern Taiwan, resulting in more than one hundred casualties and several collapsed buildings. The aftershocks occurred mostly at mid-to-lower crustal depths (10 - 30 km), related to a blind f
Externí odkaz:
https://doaj.org/article/e5f69b0a58c3406d8f2b3a83884b6560
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 24, Iss 4-2, p 685 (2013)
Signals from ten explosions were used to examine earthquake location uncertainty in Taiwan. Location errors for explosion sites determined using a relocation process were expressed in terms of statistical measurements for standard errors in the depth
Externí odkaz:
https://doaj.org/article/2f384bcedd91415e9d3c509e46386946
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 24, Iss 6, p 963 (2013)
Taiwan is known as a strongly anisotropic region observed from SKS 1 - 2 s delay time and other teleseismic phases. An estimate of the crustal contribution to the total anisotropy from the foliated Central Range is essential to understanding the over
Externí odkaz:
https://doaj.org/article/e43ddd54a2824a67ba9301ad15f421f1
Autor:
Slawomir Jack Giletycz, Fang-Yu Cai, Hao Kuo-Chen, Ireneusz Sobota, Katarzyna Greń, Zhuo-Kang Guan
It is estimated that the impact of global warming in polar regions manifests double as much as other geographical provinces around the world, and in Svalbard particularly, reaches 7 times of it. Clearly, the most observable impact of these changes co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d7a40a725fd6dc6d04edae2b04a636c1
https://doi.org/10.5194/egusphere-egu23-903
https://doi.org/10.5194/egusphere-egu23-903
Mw 6.3 and 6.0 earthquakes occurred on January 27 and 29 in 2020 in the southeastern Solomon Islands which is one of the most seismically active areas in the southern Pacific. To investigate the seismogenic mechanism and structure of the southeastern
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::70c14d63eea933f96cc0711feb1b3e5d
https://doi.org/10.5194/egusphere-egu23-11030
https://doi.org/10.5194/egusphere-egu23-11030
Deep learning has greatly improved the efficiency of earthquake detection and phase picking tasks, as demonstrated by neural network models such as PhaseNet and EQTransformer. However, the code released by these authors is not production-ready softwa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a9bc119333ff6ffe1c177342bcacf95d
https://doi.org/10.5194/egusphere-egu23-13927
https://doi.org/10.5194/egusphere-egu23-13927