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DOE OSTI · code-68879

ccp137/SUGAR

Abstract

This package (SUrface-wave Grader with ARtificial intelligence or SUGAR) automatically assigns a quality score to surface-wave seismograms (SAC format) using a trained artificial neural network model (included). Specifically, the python script 01_apply_ann.py calculates probability scores for a list of SAC files. You may consider seismograms with probability scores larger than 0.5 as acceptable data. Note no scores will be given to seismograms that do not pass an initial check (e.g., insufficient number of data points). See https://doi.org/10.1002/essoar.10507941.3 for more details.

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BibTeXRIS

Chai, Chengping [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (0000000267926014), Luo, Jingyi, Maceira, Monica [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)] (0000000312482185). 2022-01-06. ccp137/SUGAR. https://doi.org/10.11578/dc.20220106.9

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