Filling gaps in data sets or identifying outliers—that's the domain of the machine learning algorithm TabPFN, developed by a team led by Prof. Dr. Frank Hutter from the University of Freiburg ...

Global solar radiation (Hg) is a foundational input for calculating evapotranspiration, crop growth, irrigation needs, and ...

To help researchers better predict high-yielding crop traits, a team have stacked together six high-powered, machine learning algorithms that are used to interpret hyperspectral data -- and they ...

The study sheds light on the widespread use of CPS in crop management, smart greenhouses, precision irrigation, livestock ...

A new machine-learning model for predicting crop yield using environmental data and genetic information can be used to develop new, higher-performing crop varieties.

The era of predictive modeling enhanced with machine learning and artificial intelligence (AI) to aid clinical ...

River flow: New machine learning methods could improve environmental predictions Algorithm is 'taught' rules of the physical world to help researchers make better predictions Date: June 23, 2021 ...

A novel genotype-by-environmental interaction machine-learning model can predict crop yield with environmental data and genetic information more efficiently and accurately than an established model.