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Akademický článek

Magnetopause location modeling using machine learning: inaccuracy due to solar wind parameter propagation

Autor: M. Aghabozorgi Nafchi, F. Němec, G. Pi, Z. Němeček, J. Šafránková, K. Grygorov, J. Šimůnek, T.-C. Tsai

Publikováno v: Frontiers in Astronomy and Space Sciences, Vol 11 (2024)

An intrinsic limitation of empirical models of the magnetopause location is a predefined magnetopause shape and assumed functional dependences on relevant parameters. We overcome this limitation using a machine learning approach (artificial neural ne

Externí odkaz: https://doaj.org/article/8142144235d64c48b30dfe9e639a7d16

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Akademický článek

Triggered Emissions of Kinetic Alfvén Waves and Parallel Ion Cyclotron Waves by Ion Beam Mode in the Solar Wind

Autor: L. Xiang, K. H. Lee, L. C. Lee, D. J. Wu, L. Chen, H. Q. Feng, G. Q. Zhao, T. C. Tsai

Publikováno v: The Astrophysical Journal, Vol 976, Iss 2, p 184 (2024)

Kinetic Alfvén waves (KAWs) and ion cyclotron waves (ICWs) are believed to play a significant role in the solar wind heating and acceleration and are pervasive in space and astrophysical plasmas. However, the generation mechanism for the coexistence

Externí odkaz: https://doaj.org/article/747b6c5b75e043f5b854f584782ce06f

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Akademický článek

Unstructured-grid approach to develop high-fidelity groundwater model to understand groundwater flow and storage responses to excessive groundwater withdrawals in the Southern Hills aquifer system in southeastern Louisiana (USA)

Autor: Ye-Hong Chen, Hamid Vahdat-Aboueshagh, Frank T.-C. Tsai, Alyssa Dausman, Michael C. Runge

Publikováno v: Journal of Hydrology: Regional Studies, Vol 46, Iss , Pp 101342- (2023)

Study region: The Southern Hills aquifer system (SHAS) in the Louisiana Capital Area Groundwater Conservation District (CAGCD), USA. Study focus: The SHAS provides abundant groundwater for public and industrial supplies in the CAGCD. Groundwater depl

Externí odkaz: https://doaj.org/article/a38fb20b3dce4f7d87b638bfc25e4007

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Akademický článek

Accounting for uncertainty in complex alluvial aquifer modeling by Bayesian multi-model approach

Autor: Yin, Jina, T.-C. Tsai, Frank, Kao, Shih-Chieh

Publikováno v: In Journal of Hydrology October 2021 601

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Akademický článek

Deep Learning of Detecting Ionospheric Precursors Associated With M ≥ 6.0 Earthquakes in Taiwan

Autor: T. C. Tsai, H. K. Jhuang, Y. Y. Ho, L. C. Lee, W. C. Su, S. L. Hung, K. H. Lee, C. C. Fu, H. C. Lin, C. L. Kuo

Publikováno v: Earth and Space Science, Vol 9, Iss 9, Pp n/a-n/a (2022)

Abstract A short‐term (30 days before an earthquake) prediction of an earthquake is a big challenge in seismology. As a first step, we apply deep learning to the ionospheric total electron content (TEC) data between 2003 and 2014 to detect the seis

Externí odkaz: https://doaj.org/article/2db2127282eb4c51ac3b6b92013a51dc

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Akademický článek

Irrigation-Intensive Groundwater Modeling of Complex Aquifer Systems Through Integration of Big Geological Data

Autor: Hamid Vahdat-Aboueshagh, Frank T.-C. Tsai, Dependra Bhatta, Krishna P. Paudel

Publikováno v: Frontiers in Water, Vol 3 (2021)

This study identifies hydrogeologic characteristics of complex aquifers based on constructing stratigraphic structure with large, non-uniform well log data. The approach was validated through a modeling study of the irrigation-intensive Chicot aquife

Externí odkaz: https://doaj.org/article/b71f227460334cd2ba8f52c92c65cee5

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Akademický článek

Understanding impacts of groundwater dynamics on flooding and levees in Greater New Orleans

Autor: Shuo Yang, Frank T.-C. Tsai

Publikováno v: Journal of Hydrology: Regional Studies, Vol 32, Iss , Pp 100740- (2020)

Study region: The Greater New Orleans in southeastern Louisiana, USA. Study focus: Flooding is a major threat to New Orleans due to its geographic location and geologic condition. However, potential groundwater flooding is seldom studied and poorly u

Externí odkaz: https://doaj.org/article/0dee9c9044d54f6e9f6a878d16b050d2

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