Predicting the time, location and magnitude of an earthquake is a challenging job as an
earthquake does not show specific patterns resulting in inaccurate predictions. Techniques …

The low predictability of earthquakes and the high uncertainty associated with their forecasts
make earthquakes one of the worst natural calamities, capable of causing instant loss of life …

Earthquakes occur all around the world, causing varying degrees of damage and
destruction. Earthquakes are by their very nature a sudden phenomenon and predicting …

Given the robust nonlinear regression capabilities of Artificial Intelligence (AI) technology, its
commendable performance in numerous geophysical tasks is expected. Yet, AI technology …

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 …

The ARIMA method, time series analysis technique, was proposed to perform short-term
ionospheric Total Electron Content (TEC) forecast and to detect TEC anomalies. The …

Several efforts have been made to understand the complex physical processes involved in a
seismic process, but the findings are vague considering prediction capabilities …

The paper presents the author's vision of the problem of earthquake hazards from the
physical point of view. The first part is concerned with the processes of precursor's …

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 …

The ionosphere shows regular changes such as daily, 27 days, seasonal, semi-annual,
annual, and 11 years. These changes can be modeled and their effects largely determined …