A Multi-Input Convolutional Neural Networks Model for Earthquake Precursor Detection Based on Ionospheric Total Electron Content
Earthquakes occur all around the world, causing varying degrees of damage and
destruction. Earthquakes are by their very nature a sudden phenomenon and predicting …
destruction. Earthquakes are by their very nature a sudden phenomenon and predicting …
GNSS TEC-based earthquake ionospheric perturbation detection using a novel deep learning framework
In this article, a new method for seismic ionospheric Global Navigation Satellite System
(GNSS) total electron content (TEC) based anomaly detection using a deep learning …
(GNSS) total electron content (TEC) based anomaly detection using a deep learning …
Comparisons of autoregressive integrated moving average (ARIMA) and long short term memory (LSTM) network models for ionospheric anomalies detection: a study …
Since ionospheric variability changes dramatically before the major earthquakes (EQ), the
detection of ionospheric anomalies for EQ forecasting has been a hot topic for modern-day …
detection of ionospheric anomalies for EQ forecasting has been a hot topic for modern-day …
Atmospheric and ionospheric disturbances associated with the M> 6 earthquakes in the East Asian sector: A case study of two consecutive earthquakes in Taiwan
Abstract The phenomenon of Lithosphere-Ionosphere coupling is a popular topic for
researchers for the last two decades. This study aims to analyze the seismo-ionospheric …
researchers for the last two decades. This study aims to analyze the seismo-ionospheric …
A Multi-Network based Hybrid LSTM model for ionospheric anomaly detection: A case study of the Mw 7.8 Nepal earthquake
Abstract We propose a Multi-Network-based Hybrid Long Short Term Memory (N-LSTM)
model for ionospheric anomaly detection to forecast highly irregular data of the ionospheric …
model for ionospheric anomaly detection to forecast highly irregular data of the ionospheric …
Anomalies in Infrared Outgoing Longwave Radiation Data before the Yangbi Ms6.4 and Luding Ms6.8 Earthquakes Based on Time Series Forecasting Models
J Zhu, K Sun, J Zhang - Applied Sciences, 2023 - mdpi.com
Numerous scholars have used traditional thermal anomaly extraction methods and time
series prediction models to study seismic anomalies based on longwave infrared radiation …
series prediction models to study seismic anomalies based on longwave infrared radiation …
Multi-step prediction of main pump leakage in nuclear power plants with an additive model
Y Xiao, J Liu, Q Su - Progress in Nuclear Energy, 2023 - Elsevier
With the global demand of clean and low-carbon emission energy sources, safety in the
nuclear power industry has gained widespread attention. The accurate and timely long-term …
nuclear power industry has gained widespread attention. The accurate and timely long-term …
Ionospheric anomalies related to the Mw 6.5 Samar, Philippines earthquake
E Eroglu - Acta Geophysica, 2023 - Springer
Abstract Models belonging to the ionosphere that is directly affected by factors such as solar
activity, geomagnetic storm, earthquake, seasonal changes, and geographical location need …
activity, geomagnetic storm, earthquake, seasonal changes, and geographical location need …
Pre-earthquake ionospheric perturbation analysis using deep learning techniques
It has been observed in many studies that ionosphere create a significant perturbation
before major earthquakes. Therefore, forecasting of earthquakes on the basis of the …
before major earthquakes. Therefore, forecasting of earthquakes on the basis of the …
A study of ionospheric anomaly detection before the August 14, 2021 Mw7. 2 earthquake in Haiti based on sliding interquartile range method
D Chen, D Meng, F Wang, Y Gou - Acta Geodaetica et Geophysica, 2023 - Springer
This study focuses on the possible ionospheric anomalies before the Mw7. 2 earthquake in
Haiti on August 14, 2021. Based on the dual-frequency observation data of Global …
Haiti on August 14, 2021. Based on the dual-frequency observation data of Global …