FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3208869780> ?p ?o ?g. }

• W3208869780 endingPage "12" @default.
• W3208869780 startingPage "1" @default.
• W3208869780 abstract "Wavefield reconstruction inversion (WRI) formulates a PDE-constrained optimization problem to reduce cycle skipping in full-waveform inversion (FWI). WRI often requires expensive matrix inversions to reconstruct frequency-domain wavefields. Physics-informed neural network (PINN) uses the underlying physical laws as loss functions to train the neural network (NN), and it has shown its effectiveness in solving the Helmholtz equation and generating Green's functions, specifically for the scattered wavefield. By including a data-constrained term in the loss function, the trained NN can reconstruct a wavefield that simultaneously fits the recorded data and satisfies the Helmholtz equation for a given initial velocity model. Using the predicted wavefields, we rely on a small-size NN to predict the velocity using the reconstructed wavefield. In this velocity prediction NN, spatial coordinates are used as input data to the network and the scattered Helmholtz equation is used to define the loss function. After we train this network, we are able to predict the velocity in the domain of interest. We develop this PINN-based WRI method and demonstrate its potential using a part of the Sigsbee2A model and a modified Marmousi model. The results show that the PINN-based WRI is able to invert for a reasonable velocity with very limited iterations and frequencies, which can be used in a subsequent FWI application." @default.
• W3208869780 created "2021-11-08" @default.
• W3208869780 creator A5020237777 @default.
• W3208869780 creator A5032021877 @default.
• W3208869780 date "2022-01-01" @default.
• W3208869780 modified "2023-10-17" @default.
• W3208869780 title "Wavefield Reconstruction Inversion via Physics-Informed Neural Networks" @default.
• W3208869780 cites W1903160458 @default.
• W3208869780 cites W1910501430 @default.
• W3208869780 cites W1997075890 @default.
• W3208869780 cites W2009552164 @default.
• W3208869780 cites W2028189898 @default.
• W3208869780 cites W2045642993 @default.
• W3208869780 cites W2047421614 @default.
• W3208869780 cites W2051434435 @default.
• W3208869780 cites W2060133113 @default.
• W3208869780 cites W2080308818 @default.
• W3208869780 cites W2083841243 @default.
• W3208869780 cites W2100245965 @default.
• W3208869780 cites W2101615520 @default.
• W3208869780 cites W2139381422 @default.
• W3208869780 cites W2165698076 @default.
• W3208869780 cites W2213612645 @default.
• W3208869780 cites W2326199831 @default.
• W3208869780 cites W2331422999 @default.
• W3208869780 cites W2522338163 @default.
• W3208869780 cites W2525748878 @default.
• W3208869780 cites W2749028154 @default.
• W3208869780 cites W2767933350 @default.
• W3208869780 cites W2799565130 @default.
• W3208869780 cites W2803629276 @default.
• W3208869780 cites W2804813293 @default.
• W3208869780 cites W2889523591 @default.
• W3208869780 cites W2891932361 @default.
• W3208869780 cites W2896907026 @default.
• W3208869780 cites W2899283552 @default.
• W3208869780 cites W2911424749 @default.
• W3208869780 cites W2912052494 @default.
• W3208869780 cites W2913170515 @default.
• W3208869780 cites W2914917628 @default.
• W3208869780 cites W2915004230 @default.
• W3208869780 cites W2951392159 @default.
• W3208869780 cites W2955412401 @default.
• W3208869780 cites W2970230279 @default.
• W3208869780 cites W2982937153 @default.
• W3208869780 cites W2985630280 @default.
• W3208869780 cites W2988434973 @default.
• W3208869780 cites W2995926383 @default.
• W3208869780 cites W3003922491 @default.
• W3208869780 cites W3004375581 @default.
• W3208869780 cites W3005407459 @default.
• W3208869780 cites W3005771615 @default.
• W3208869780 cites W3008118574 @default.
• W3208869780 cites W3008181685 @default.
• W3208869780 cites W3011245630 @default.
• W3208869780 cites W3014029212 @default.
• W3208869780 cites W3015170749 @default.
• W3208869780 cites W3015865829 @default.
• W3208869780 cites W3032032710 @default.
• W3208869780 cites W3034433715 @default.
• W3208869780 cites W3047035577 @default.
• W3208869780 cites W3089539538 @default.
• W3208869780 cites W3090979856 @default.
• W3208869780 cites W3091352727 @default.
• W3208869780 cites W3091622848 @default.
• W3208869780 cites W3091672556 @default.
• W3208869780 cites W3102747040 @default.
• W3208869780 cites W3104564825 @default.
• W3208869780 cites W3121371611 @default.
• W3208869780 cites W3122977429 @default.
• W3208869780 cites W3123973360 @default.
• W3208869780 cites W3124477118 @default.
• W3208869780 cites W3154969878 @default.
• W3208869780 cites W3161445736 @default.
• W3208869780 cites W3211225070 @default.
• W3208869780 cites W4233837401 @default.
• W3208869780 doi "https://doi.org/10.1109/tgrs.2021.3123122" @default.
• W3208869780 hasPublicationYear "2022" @default.
• W3208869780 type Work @default.
• W3208869780 sameAs 3208869780 @default.
• W3208869780 citedByCount "19" @default.
• W3208869780 countsByYear W32088697802021 @default.
• W3208869780 countsByYear W32088697802022 @default.
• W3208869780 countsByYear W32088697802023 @default.
• W3208869780 crossrefType "journal-article" @default.
• W3208869780 hasAuthorship W3208869780A5020237777 @default.
• W3208869780 hasAuthorship W3208869780A5032021877 @default.
• W3208869780 hasBestOaLocation W32088697802 @default.
• W3208869780 hasConcept C11413529 @default.
• W3208869780 hasConcept C121332964 @default.
• W3208869780 hasConcept C127313418 @default.
• W3208869780 hasConcept C134306372 @default.
• W3208869780 hasConcept C135252773 @default.
• W3208869780 hasConcept C154945302 @default.
• W3208869780 hasConcept C165205528 @default.
• W3208869780 hasConcept C182310444 @default.
• W3208869780 hasConcept C18591234 @default.
• W3208869780 hasConcept C1893757 @default.

• next