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

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

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 ...

While demand planning accuracy currently hovers around 60%, DLA officials aim to push that baseline figure to 85% with the help of AI and ML tools. Improved forecasting will ensure the services have ...

Ph.D. student Phillip Si and Assistant Professor Peng Chen developed Latent-EnSF, a technique that improves how ML models assimilate data to make predictions.

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

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 ...

Financial forecasting is the act of estimating future financial outcomes for a business or an investment. It is a critical process in financial planning and decision-making. It employs statistical ...

Accurately predicting the weather is hard — really hard, but a new AI-powered forecast model just hit a milestone that has experts saying your forecast could soon get more accurate, and further out, ...

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