Legacy load forecasting models are struggling with ever-more-common, unpredictable events; power-hungry AI offers a solution.
Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case ...
Oversimplifies trends and ignores real-world disruptions. Can’t predict economic downturns, competitor actions and shifts in customer behavior on its own. Ignores randomness; every forecast will have ...
Abstract: In the aviation industry, inventory management based on non-smooth demand forecasting is an ongoing challenge. Generally, aircraft parts lack easily observable demand patterns. Through ...
Abstract: The transition of the automotive sector to electric vehicles (EVs) necessitates research on charging demand forecasting for optimal station placement and capacity planning. In the literature ...
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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 ...
A new AI tool to predict the spread of infectious disease outperforms existing state-of-the-art forecasting methods. The tool, created with federal support by researchers at Johns Hopkins and Duke ...
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