Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

As climate extremes intensify across Africa, the need for accurate and timely weather prediction has become increasingly ...

Demand forecasting methods have been used in retail for a long time. Most of them are based on historical data, which is no longer useful in the new COVID-19 reality. If you used an ML-powered demand ...

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%, ...

Forecasting macroeconomic variables is key to developing a view on a country's economic outlook. Most traditional forecasting models rely on fitting data to a pre-specified relationship between input ...