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 ...

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

AI fixes earnings forecasting when it expands coverage, standardizes signal extraction, and quantifies uncertainty. AI breaks forecasting when it creates false precision, synchronized expectations, ...

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

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 ...

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 ...

One of the unwritten axioms of data scientists specializing in machine learning methodologies is that they all try their hand at predicting the stock market. Some of the best attempts have turned a ...

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

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 ...