Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

Put down the pen and paper and shelve the spreadsheets. Artificial intelligence (AI) and advanced machine learning are the next-generation tools for demand forecasting in distribution. That was the ...

A University of Manchester researcher has developed a machine-learning method to spot sudden changes in fluid behavior, known as bifurcation points, before traditional simulations fail. The approach ...

Artificial intelligence-driven algorithms can be used to better forecast models for natural disasters, saving lives and protecting property by rapidly analyzing massive data sets and identifying ...

Researchers have developed a feature selection-based solar irradiance forecasting method to improve the operation of ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

From idle production lines to costly rush orders, poor spare parts forecasting can cripple operations. New AI, statistical models, and integrated tracking systems are helping companies predict demand ...

Artificial intelligence (AI) is emerging as a powerful tool to predict food consumption patterns and guide policy decisions, ...

As the PPC landscape continues to evolve, having the ability to predict future campaign performance is invaluable. This article will cover some of my favorite PPC forecasting techniques using Google ...