A new research paper shows the approach performs significantly better than the random-walk forecasting method.

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 ...

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 ...

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 ...

Forecasting inflation has become a major challenge for central banks since 2020, due to supply chain disruptions and economic uncertainty post-pandemic. Machine learning models can improve forecasting ...

This study was led by Professor Qi Zhong and Professor Xiuping Yao from the China Meteorological Administration Training Center, and Assistant Engineer Zhicha Zhang from the Zhejiang Meteorological ...

Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...

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 ...

Machine learning reduces friction at every stage of a business, whether you’re coming up with new product ideas or getting the goods delivered to the client. It increases business efficiency, improves ...