{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,14]],"date-time":"2025-10-14T00:37:01Z","timestamp":1760402221063,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2021,3,30]],"date-time":"2021-03-30T00:00:00Z","timestamp":1617062400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shenzhen science &amp;technology","award":["JCYJ20190808161401653"],"award-info":[{"award-number":["JCYJ20190808161401653"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>To verify the relationship between AETA (Acoustic and Electromagnetics to Artificial Intelligence (AI)) electromagnetic anomalies and local earthquakes, we have performed statistical studies on the electromagnetic data observed at AETA station. To ensure the accuracy of statistical results, 20 AETA stations with few data missing and abundant local earthquake events were selected as research objects. A modified PCA method was used to obtain the sequence representing the signal anomaly. Statistical results of superposed epoch analysis have indicated that 80% of AETA stations have significant relationship between electromagnetic anomalies and local earthquakes. These anomalies are more likely to appear before the earthquakes rather than after them. Further, we used Molchan\u2019s error diagram to evaluate the electromagnetic signal anomalies at stations with significant relationships. All area skill scores are greater than 0. The above results have indicated that AETA electromagnetic anomalies contain precursory information and have the potential to improve local earthquake forecasting.<\/jats:p>","DOI":"10.3390\/e23040411","type":"journal-article","created":{"date-parts":[[2021,3,31]],"date-time":"2021-03-31T00:13:10Z","timestamp":1617149590000},"page":"411","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Statistical Analysis of the Relationship between AETA Electromagnetic Anomalies and Local Earthquakes"],"prefix":"10.3390","volume":"23","author":[{"given":"Qinmeng","family":"Guo","sequence":"first","affiliation":[{"name":"The Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, China"},{"name":"Shenzhen Earthquake Monitoring and Prediction Technology Research Center, Peking University Shenzhen Graduate School, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shanshan","family":"Yong","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, China"},{"name":"Shenzhen Earthquake Monitoring and Prediction Technology Research Center, Peking University Shenzhen Graduate School, Shenzhen 518055, China"},{"name":"Engineering Department, Shenzhen MSU-BIT University, Shenzhen 518172, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xin\u2019an","family":"Wang","sequence":"additional","affiliation":[{"name":"The Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, China"},{"name":"Shenzhen Earthquake Monitoring and Prediction Technology Research Center, Peking University Shenzhen Graduate School, Shenzhen 518055, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,3,30]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"A Summary of Electromagnetic Anomalies before Earthquakes","volume":"38","author":"Cai","year":"2018","journal-title":"South China J. 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