Earthquake is one the most important disasters in the world. In order to save lives and building substructures of countries, more research in this field should be carried out as a matter of severity. Computer modeling and different artificial intelligence algorithms are known as applicable tools for the earthquake hazards prediction and prevention. This article tries to review the recent studie...

The Collaboratory for the Study of Earthquake Predictability (CSEP) aims to advance earthquake research by rigorous testing of earthquake forecast hypotheses. As in other disciplines, such hypothesis testing requires carefully designed experiments that meet certain requirements: they should be reproducible, fully transparent, and conducted within a controlled environment. CSEP has begun buildin...

Our research focuses on computational techniques to understand the dynamics of space-time patterns in driven threshold systems, particularly on earthquake fault systems. We discuss the scientific and computational formulation of strategies for understanding such spacetime patterns, leading optimistically to earthquake forecasting and prediction. In particular, we describe pattern dynamics techn...

Earthquake is one of the most destructive natural phenomena which has human and financial losses. The existence of an efficient prediction system and early warning system will be useful for reducing effects of destroying earthquake. In this research, the soil temperature time-series data, obtained from three meteorological station, using three filters (Fourier, Wavelet and Logarithmic Different...

There is anecdotal evidence for profound behavioral changes prior to and during earthquakes in many organisms, including arthropods such as ants. Behavioral or physiological analysis has often, in light of these reports, been proposed as a means of earthquake prediction. We report here a serendipitous study of the effect of the powerful Landers earthquake in the Mojave Desert, USA (Richter magn...

A UK-based grid computing project that merges two earthquake data modeling methods is one of the latest tools in earthquake prediction. The new technique provides a 2D data map of tectonic structures by combining a macro modeling method based on surface deformation measurements from satellite imagery with a micro method based on finite element analysis and simulation within local geophysical co...

The use of different probability distributions as described by the Exponential, Pareto, Lognormal, Rayleigh, and Gama probability functions applied to estimation the time of the next great earthquake (Ms≥6.0) in different seismotectonic provinces of Iran. This prediction is based on the information about past earthquake occurrences in the given region and the basic assumption that future seismi...

The ultimate goal of earthquake early warning (EEW) is to provide local shaking information to users before the strong shaking from an earthquake reaches their location. This is accomplished by operating one or more real-time analyses that attempt to predict shaking intensity, often by estimating the earthquake’s location and magnitude and then predicting the ground motion from that point sourc...