Výsledky vyhledávání - "Junliu Suwen"

Joint Inversion of Receiver Function and Surface Wave Dispersion by Hamiltonian Monte Carlo Sampling

Autor: Junliu Suwen, Qi-Fu Chen, Nanqiao Du

Publikováno v: Seismological Research Letters. 94:369-384

We have proposed a new probabilistic inversion method to perform the joint inversion of receiver function and surface wave dispersion data. In this method, we apply the Hamiltonian dynamics in the Bayesian framework to efficiently sample the posterio

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::df50dcb650d5fedd42a253db599a4c3d
https://doi.org/10.1785/0220220044

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Full-wave anisotropy tomography for the upper mantle of Northeast China using SKS splitting intensities

Autor: Junliu Suwen, Yi Lin, Li Zhao, Qi-Fu Chen

Northeast (NE) China is located in the eastern Central Asian Orogenic Belt, and has a complex deformation history. The evolution of NE China has been controlled by the (Paleo-)Pacific Plate since the late Mesozoic and was affected by the closure of t

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f01057c6fb703401ae9cb5229812a523
https://doi.org/10.5194/egusphere-egu23-4746

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The extended range phase shift method for broadband surface wave dispersion measurement from ambient noise and its application in ore deposit characterization

Autor: Bao Deng, Junlun Li, Jiangshan Liu, Changming Shen, Junliu Suwen, Qi-Fu Chen

Publikováno v: GEOPHYSICS. 87:JM29-JM40

Surface wave tomography using seismic ambient noise has been applied widely in subsurface characterization, the depth of which ranges from a few meters in urban underground engineering to tens of kilometers in delineation of crustal heterogeneities.

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::32506e818bc10fa2d3628b80f9136e3a
https://doi.org/10.1190/geo2021-0320.1

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Multi-task unscented Kalman inversion (MUKI): a derivative-free joint inversion framework and its application to joint inversion of geophysic

Autor: Longlong Wang, Yun Chen, Youshan Liu, Nanqiao Du, Wei Li, Junliu Suwen

Unscented Kalman inversion is a novel method that uses unscented Kalman filter to solve inverse problems. This paper applies it to inverse multiple geophysical observations simultaneously (i.e., Multi-task unscented Kalman inversion (MUKI)). In this

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::9d5d9136e36bd71f372b832407a3b0fd
https://doi.org/10.1002/essoar.10512157.3

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Multi-task unscented Kalman inversion (MUKI): a derivative-free joint inversion framework and its application to joint inversion of geophysical data

Autor: Longlong Wang, Yun Chen, Youshan Liu, Nanqiao Du, Wei Li, Junliu Suwen

In the geophysical joint inversion, the gradient and Bayesian Markov Chain Monte Carlo (MCMC) sampling-based methods are widely used owing to their fast convergences or global optimality. However, these methods either require the computation of gradi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1b8768e3a28225b8d2b02d77e716ce41

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