首页|Researchers' Work from University of Science and Technology of China Focuses on Machine Learning (Monitoring seismicity in the southern Sichuan Basin using a machine learning workflow)
Researchers' Work from University of Science and Technology of China Focuses on Machine Learning (Monitoring seismicity in the southern Sichuan Basin using a machine learning workflow)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
Researchers detail new data in artificial intelligence. According to news reporting from Hefei, People's Republic of China, by NewsRx journalists, research stated, "Monitoring seismicity in real time provides significant benefits for timely earthquake warning and analyses." Financial supporters for this research include National Key Research And Development Program of China. Our news editors obtained a quote from the research from University of Science and Technology of China: "In this study, we propose an automatic workflow based on machine learning (ML) to monitor seismicity in the southern Sichuan Basin of China. This workflow includes coherent event detection, phase picking, and earthquake location using three-component data from a seismic network. By combining PhaseNet, we develop an ML-based earthquake location model called PhaseLoc, to conduct real-time monitoring of the local seismicity. The approach allows us to use synthetic samples covering the entire study area to train PhaseLoc, addressing the problems of insufficient data samples, imbalanced data distribution, and unreliable labels when training with observed data. We apply the trained model to observed data recorded in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average differences in latitude, longitude, and depth are 5.7 km, 6.1 km, and 2 km, respectively, compared to the reference catalog."
University of Science and Technology of ChinaHefeiPeople's Republic of ChinaAsiaCyborgsEmerging TechnologiesMachine Learning
NETL
NSTL
