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

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 ...

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%, ...

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

Traditional decline curve analyses (DCAs), both deterministic and probabilistic, use specific models to fit production data for production forecasting. Various decline curve models have been applied ...

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

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 ...

Bank of America announced Friday the launch of CashPro Forecasting, an artificial intelligence (AI) and machine learning (ML) cash flow forecasting tool. It utilizes ML models based on a business's ...

NEW YORK--(BUSINESS WIRE)--KBRA Altman, a division of KBRA Analytics, is pleased to announce the launch of its new High Yield Return Forecasting Model. Unlike traditional approaches that examine ...

Scientists have developed a machine learning approach to accurately predict potentially harmful amine emissions from carbon-capturing plants. Global warming is partly due to the vast amount of carbon ...