Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction

Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction

Abstract This study explores the potential of machine learning algorithms for earthquake prediction, utilizing fluid chemical anomaly data from hot springs. Six hot springs, located within an active fault zone along the southeastern coast of China, were carefully chosen as hydrochemical monitoring s...

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Bibliographic Details
Main Authors: Ruijie Zhu, Fengtian Yang, Xiaocheng Zhou, Jiao Tian, Yongxian Zhang, Miao He, Jingchao Li, Jinyuan Dong, Ying Li
Format: Article
Language:English
Published: Wiley 2024-06-01
Series:Water Resources Research
Subjects:
earthquake prediction
hot spring
hydrogeochemical anomalies
machine learning
anomaly detection algorithms
Online Access:https://doi.org/10.1029/2023WR034748
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