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

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

DFKI has developed a system that makes agriculture more predictable, reduces risks and optimises the use of resources. With the help of satellite data and machine learning, the platform analyses ...

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

But amid all the hype, the real story that has emerged doesn’t focus on the technology itself but on the people using it ...

This study explores the development of two predictive models for the yield sooting index (YSI) of various fuels using the advanced capabilities of machine learning (ML), particularly multilayer ...

Data Preprocessing: Cleaning, normalizing, and integrating data for effective analysis. Model Development: Employing machine learning models (e.g., LSTM, ARIMA, SVM) for weather prediction, crop ...

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.