Seismological Research Letters (SRL) announces a Focus Section on Machine Learning in Seismology. Recent improvements in computational capabilities and the availability of large seismic data volume have created new opportunities for the application of machine learning tools in seismological fields. Notable applications include seismic signal detection and classification, seismic data interpolation, synthetic seismogram generation, earthquake parameter estimation, seismic noise analysis and reduction, and subsurface structure imaging. More advanced machine learning techniques and algorithms are emerging as possible new sources of scientific insights. For example, deep learning with large labeled datasets can produce superior results, and unsupervised learning has the potential to unravel hidden patterns from large-scale datasets. The application of these new techniques can help improve our understanding of Earth structure and seismic sources from a new perspective.
This SRL focus section aims to publish results from research related to machine learning and data science applications and developments in seismology. Studies can include, but are not limited to, applications of supervised or unsupervised learning tools in various seismological topics, such as structure imaging, seismic waveform processing, seismic event classification, earthquake sequence analysis, early warning, and seismic hazard mitigation.
Individuals interested in submitting contributions are strongly urged to contact the guest editors to discuss their planned contribution prior to submission.
Guest editors for this focus section are:
Karianne Bergen, Harvard University
karianne_bergen@fas.harvard.edu
Ting Chen, Los Alamos National Laboratory
tchen@lanl.gov
Zefeng Li, California Institute of Technology
zefengli@gps.caltech.edu
Important Dates:
Submission Deadline: October 1, 2018 (early submissions are encouraged and will be processed immediately after the submission)
Acceptance Deadline: January 1 2019
Published Issue: SRL March-April 2019
Submit manuscripts via SRL Editorial Manager at http://srl.edmgr.com using the article type “Machine Learning in Seismology Focus Section”. Detailed instructions on how to prepare an SRL manuscript can be found at https://www.seismosoc.org/publications/srl/srl-authorsinfo/.
Note that the recommended length for SRL focus-section articles is up to 3000 words for the main text plus table and figure captions; this 3000 words does not include the title, author affiliation, abstract, and references. Longer papers may be submitted at the discretion of the editor. Articles accepted to the SRL Focus Section on the Machine Learning in Seismology will be published online ahead of print.
Address questions about scientific issues to the guest editors or SRL Editor-in-Chief Zhigang Peng at srleditor@seismosoc.org. Address questions about submissions to SRL Managing Editor Mary George at srl@seismosoc.org.