Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been thought to forebode earthquakes are not supported by empirical evidence. As ...

A team at Los Alamos National Laboratory used machine learning — an application of artificial intelligence — to detect the hidden signals that precede an earthquake. The findings at the Kīlauea ...

For more than 30 years, the models that researchers and government agencies use to forecast earthquake aftershocks have remained largely unchanged. While these older models work well with limited data ...

STATESBORO, Ga., Oct. 25, 2024 (GLOBE NEWSWIRE) -- Cemil Emre Yavas and his research team have achieved a remarkable 97.97% accuracy in earthquake prediction for Los Angeles, a high-risk seismic zone, ...

An international team of researchers recently examined the potential for new a model for predicting earthquake aftershocks using a subset of machine learning known as deep learning. While government ...

When talking about squeezing rocks together, Prof. Gregory McLaskey Ph.D ’05, civil engineering, gets a glimmer in his eyes. Using the world’s largest rock squeezing machine, McLaskey researches the ...

Georgia Southern University researchers develop a machine learning model with 97.97% accuracy in earthquake forecasting. STATESBORO, GA, UNITED STATES, October 29 ...

Scientists have built a lab model that visually tracks how microscopic contact points between fault surfaces evolve during earthquake cycles, revealing the hidden mechanics behind both the slow ...

AIR Worldwide Releases Updated Earthquake Model for the United States Newly added induced seismicity module captures the effects of human activity BOSTON, June 19, 2017 - Catastrophe risk modeling ...

This map depicts the predicted types of soil in Tokyo with an unprecedented level of detail. Such maps are essential for urban planning and earthquake risk assessment, as they reveal areas that are ...