An Earthquake Forecast Model Based on Multi-Station PCA Algorithm
With the continuous development of human society, earthquakes are becoming more and more dangerous to the production and life of human society. Researchers continue to try to predict earthquakes, but the results are still not significant. With the development of data science, sensing and communicati...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/7/3311 |
| _version_ | 1797440514671247360 |
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| author | Yibin Liu Shanshan Yong Chunjiu He Xin’an Wang Zhenyu Bao Jinhan Xie Xing Zhang |
| author_facet | Yibin Liu Shanshan Yong Chunjiu He Xin’an Wang Zhenyu Bao Jinhan Xie Xing Zhang |
| author_sort | Yibin Liu |
| collection | DOAJ |
| description | With the continuous development of human society, earthquakes are becoming more and more dangerous to the production and life of human society. Researchers continue to try to predict earthquakes, but the results are still not significant. With the development of data science, sensing and communication technologies, there are increasing efforts to use machine learning methods to predict earthquakes. Our work raises a method that applies big data analysis and machine learning algorithms to earthquakes prediction. All data are accumulated by the Acoustic and Electromagnetic Testing All in One System (AETA). We propose the multi-station Principal Component Analysis (PCA) algorithm and extract features based on this method. At last, we propose a weekly-scale earthquake prediction model, which has a 60% accuracy using LightGBM (LGB). |
| first_indexed | 2024-03-09T12:09:17Z |
| format | Article |
| id | doaj.art-0bdb38a1d2b648a8b24655e44f9768f9 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T12:09:17Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-0bdb38a1d2b648a8b24655e44f9768f92023-11-30T22:53:59ZengMDPI AGApplied Sciences2076-34172022-03-01127331110.3390/app12073311An Earthquake Forecast Model Based on Multi-Station PCA AlgorithmYibin Liu0Shanshan Yong1Chunjiu He2Xin’an Wang3Zhenyu Bao4Jinhan Xie5Xing Zhang6The Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, ChinaThe Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, ChinaThe Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, ChinaThe Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, ChinaThe Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, ChinaThe Key Laboratory of Integrated Microsystems, Peking University Shenzhen Graduate School, Shenzhen 518055, ChinaSchool of Software and MicroElectronics, Peking University, Beijing 100871, ChinaWith the continuous development of human society, earthquakes are becoming more and more dangerous to the production and life of human society. Researchers continue to try to predict earthquakes, but the results are still not significant. With the development of data science, sensing and communication technologies, there are increasing efforts to use machine learning methods to predict earthquakes. Our work raises a method that applies big data analysis and machine learning algorithms to earthquakes prediction. All data are accumulated by the Acoustic and Electromagnetic Testing All in One System (AETA). We propose the multi-station Principal Component Analysis (PCA) algorithm and extract features based on this method. At last, we propose a weekly-scale earthquake prediction model, which has a 60% accuracy using LightGBM (LGB).https://www.mdpi.com/2076-3417/12/7/3311earthquake forecastPCAdimensionality reductionAETA |
| spellingShingle | Yibin Liu Shanshan Yong Chunjiu He Xin’an Wang Zhenyu Bao Jinhan Xie Xing Zhang An Earthquake Forecast Model Based on Multi-Station PCA Algorithm Applied Sciences earthquake forecast PCA dimensionality reduction AETA |
| title | An Earthquake Forecast Model Based on Multi-Station PCA Algorithm |
| title_full | An Earthquake Forecast Model Based on Multi-Station PCA Algorithm |
| title_fullStr | An Earthquake Forecast Model Based on Multi-Station PCA Algorithm |
| title_full_unstemmed | An Earthquake Forecast Model Based on Multi-Station PCA Algorithm |
| title_short | An Earthquake Forecast Model Based on Multi-Station PCA Algorithm |
| title_sort | earthquake forecast model based on multi station pca algorithm |
| topic | earthquake forecast PCA dimensionality reduction AETA |
| url | https://www.mdpi.com/2076-3417/12/7/3311 |
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