{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T18:14:57Z","timestamp":1781115297535,"version":"3.54.1"},"reference-count":36,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2022,3,13]],"date-time":"2022-03-13T00:00:00Z","timestamp":1647129600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2019R1A2C1002343"],"award-info":[{"award-number":["NRF-2019R1A2C1002343"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["NRF-2020R1I1A1A01061632"],"award-info":[{"award-number":["NRF-2020R1I1A1A01061632"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The discrimination between earthquakes and artificial explosions is a significant issue in seismic analysis to efficiently prevent and respond to seismic events. However, the discrimination of seismic events is challenging due to the low incidence rate. Moreover, the similarity between earthquakes and artificial explosions with a local magnitude derives a nonlinear data distribution. To improve the discrimination accuracy, this paper proposes machine-learning-based seismic discrimination methods\u2014support vector machine, naive Bayes, and logistic regression. Furthermore, to overcome the nonlinear separation problem, the kernel functions and regularized logistic regression are applied to design seismic classifiers. To efficiently design the classifier, P- and S-wave amplitude ratios on the time domain and spectral ratios on the frequency domain, which is converted by fast Fourier transform and short-time Fourier transform are selected as feature vectors. Furthermore, an adaptive synthetic sampling algorithm is adopted to enhance the classifier performance against the seismic data imbalance issue caused by the non-equivalent number of occurrences. The comparisons among classifiers are evaluated by the binary classification performance analysis methods.<\/jats:p>","DOI":"10.3390\/s22062219","type":"journal-article","created":{"date-parts":[[2022,3,13]],"date-time":"2022-03-13T21:44:17Z","timestamp":1647207857000},"page":"2219","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Imbalanced Seismic Event Discrimination Using Supervised Machine Learning"],"prefix":"10.3390","volume":"22","author":[{"given":"Hyeongki","family":"Ahn","sequence":"first","affiliation":[{"name":"Department of Electrical Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sangkyeum","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Electrical Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kyunghyun","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Electrical Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahyeong","family":"Choi","sequence":"additional","affiliation":[{"name":"Department of Electrical Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6438-8823","authenticated-orcid":false,"given":"Kwanho","family":"You","sequence":"additional","affiliation":[{"name":"Department of Electrical Computer Engineering, Sungkyunkwan University, Suwon 16419, Korea"},{"name":"Department of Smart Fab. Technology, Sungkyunkwan University, Suwon 16419, Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,13]]},"reference":[{"key":"ref_1","first-page":"10638","article-title":"Maginitude-based discrimination of man-made seismic events from naturally occurring earthquakes in Utah, USA","volume":"4","author":"Koper","year":"2016","journal-title":"Geophys. Res. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1029\/2018JB016661","article-title":"Reliable real-time seismic signal\/noise discrimination with machine learning","volume":"124","author":"Meier","year":"2019","journal-title":"J. Geophys. Res.-Solid Earth"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4773","DOI":"10.1029\/2018GL077870","article-title":"Machine learning seismic wave discrimination: Application to earthquake early warning","volume":"45","author":"Li","year":"2018","journal-title":"Geophys. Res. 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