Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...
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 ...
Demand forecasting methods have been used in retail for a long time. Most of them are based on historical data, which is no longer useful in the new COVID-19 reality. If you used an ML-powered demand ...
Drawing on research, ESMT’s Oliver Binz shows why breaking profitability into its underlying drivers — rather than treating ...
Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...
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 ...
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 ...
In a new study led by the University of Washington, researchers have demonstrated artificial intelligence's ability to improve lightning forecasts. Lightning strikes led to the devastating California ...
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