Forecasting and early warning systems are important investments to protect lives, properties,
and livelihood. While early warning systems are frequently used to predict the magnitude …

We provide an overview of the basic models of the aftershock processes and advanced
methods used to predict postseismic hazard. We consider both the physical mechanisms for …

The literature often reports space–time relations between the abnormal variations of different
kinds of nonseismological (ie, geophysical, geochemical, and atmospheric) parameters and …

Real-time integration of multi-parametric observations is expected to accelerate the process
toward improved, and operationally more effective, systems for time-Dependent Assessment …

Earthquake forecasts estimate the likelihood of seismic activity within a specific region over
a given timeframe, utilizing historical data and patterns from past earthquakes. In New …

The paper provides, for the first time, a long-term (> 10 years) analysis of anomalous
transients in Earth's emitted radiation over Turkey and neighbouring regions. The RST …

In this paper, we suggest two machine learning methods for seismic hazard forecast. The
first method is used for spatial forecasting of maximum possible earthquake magnitudes (M …

The results of earthquake prediction largely depend on the quality of data and the methods
of their joint processing. At present, for a number of regions, it is possible, in addition to data …

An ensemble model integrates forecasts of different models (or different parametrizations of
the same model) into one single ensemble forecast. This procedure has different names in …

In this paper, we gather and take stock of the results produced by the Operational
Earthquake Forecasting (OEF) system in Italy, during its first 10 yr of operativity. The system …