National precipitation forecasting has for decades been hamstrung by static and inadequate climate models, but new tools are ...

This prediction approach achieves higher agreement in predictions by optimizing the concordance correlation coefficient (CCC), which measures how well pairs of observations fall on the 45-degree line ...

This study presents a transfer learning–based method for predicting train-induced environmental vibration. The method applies data fusion to combine physics-based numerical simulations and limited ...

Accurately predicting complex agronomic traits remains a major bottleneck in crop breeding. This study demonstrates how optimized genomic prediction models can reliably forecast flowering time, yield ...

In order to understand currents, tides and other ocean dynamics, scientists need to accurately capture sea surface height, or ...

Statistical models predict stock trends using historical data and mathematical equations. Common statistical models include regression, time series, and risk assessment tools. Effective use depends on ...