AI models can process thousands of factors simultaneously, including demand signals across multiple items, macroeconomic ...

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 ...

The landscape of demand forecasting, data science and machine learning is rapidly evolving, as companies seek innovative approaches to handle the intricate intersection between technology and consumer ...

Michael Amori is CEO and cofounder of Virtualitics. A data scientist and entrepreneur with a background in finance and physics. Accurate demand forecasting is the linchpin of effective inventory, cost ...

What do the stock market and weather forecasting have in common? Here’s a clue: stocks are valued based on trend projections, whereas changes in weather are tracked using prevailing atmospheric ...

Researchers at Institute of Science Tokyo have developed a novel Group Encoding method that accurately forecasts electricity demand using only On/Off device data from building energy systems. Tested ...

Dr Yves R. Sagaert emphasizes the importance of organizations shifting away from traditional static budgeting, which relies ...

With legacy load forecasting models struggling with unpredictable events that are becoming ever more common, power-hungry AI ...