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 ...

The fractal-based models, targeting roughness versus regularity, were able to characterize these earthquake swarms, which the researchers believe were caused by the mix of slowly moving underground ...

The Yellowstone Caldera, spanning Wyoming, Idaho, and Montana, is among the most seismically active volcanic regions on Earth. A caldera forms when a volcano erupts, emptying the underlying magma ...

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...

“A building is only as strong as its foundation” is a common adage to signify the importance of having a stable and solid base to build upon. The type and design of foundation are important for ...

Researchers used machine learning to reanalyze Yellowstone's historical earthquake data, revealing that humans may have missed a few things. Reading time 2 minutes Before the advent of artificial ...

Kyoto, Japan -- 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 ...

The public could have days or months of warning about a major earthquake through identification of prior low-level tectonic unrest over large areas, according to research by scientists who analyzed ...