Picture a single forecasting mistake triggering a cascade of negative consequences, such as surplus inventory, strained supplier relationships and disappointed customers. In today's world, accurate ...

The study departs from conventional mean-based economic forecasting by focusing on quantile prediction, a technique that ...

During an epidemic, some of the most critical questions for healthcare decision-makers are the hardest ones to answer: When ...

Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, ...

Recent advances in forecasting demand within emergency departments (EDs) have been bolstered by the integration of machine learning and time series analytical techniques. The objective of these ...

A comprehensive framework integrates statistical modeling, machine learning, and simulation to optimize urban traffic forecasting, capacity ...

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 ...

An operational solar farm in Australia, where the study took place. Image: Nextracker. Machine learning techniques have been used in a study to boost the accuracy of renewables forecasts by up to 45%, ...

In a new study led by the University of Washington, researchers have demonstrated artificial intelligence's ability to improve lightning forecasts. Lightning strikes led to the devastating California ...

With chatbots like ChatGPT making a splash, machine learning is playing an increasingly prominent role in our lives. For many of us, it’s been a mixed bag. We rejoice when our Spotify For You playlist ...

Miguel Jimenez receives funding from the National Aeronautics and Space Administration. With chatbots like ChatGPT making a splash, machine learning is playing an increasingly prominent role in our ...