In this study we determined neural network weights and biases by Imperialist Competitive Algorithm (ICA) in order to train network for predicting earthquake intensity in Richter. For this reason, we used dependent parameters like earthquake occurrence time, epicenter’s latitude and longitude in degree, focal depth in kilometer, and the seismological center distance from epicenter and earthquake...

Earthquake is one of the major natural calamity. So prediction of the reach of earthquake event to the various locations could result in minimizing the disaster due to it. This system contains the design of sensor system and the techniques used for detection and processing of the received signals in real time. In this system, an earthquake which is also known as a tremor or temblor is the resul...

Earthquake prediction has two potentially compatible but distinctly different objectives: (a) phenomena that provide information about the future earthquake hazard useful to those who live in earthquake-prone regions and (b) phenomena causally related to the physical processes governing failure on a fault that will improve our understanding of those processes. For seismic hazard analysis in Vra...

Many streams and springs, which were dry or nearly dry before the 2014 Mw6.0 South Napa earthquake, started to flow after the earthquake. A United States Geological Survey stream gauge also registered a coseismic increase in discharge. Public interest was heightened by a state of extreme drought in California. Since the new flows were not contaminated by pre-existing surface water, their compos...