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 ...
Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...
From new tariffs and trade uncertainty to geopolitical tension and extreme weather events, external forces have upended traditional demand forecasting approaches. Among those most impacted are the CPG ...
What if you could predict the future—not just in abstract terms, but with actionable precision? From forecasting energy demand to anticipating retail trends, the ability to make accurate predictions ...
The intermittent nature of solar energy poses challenges to grid stability, making accurate ultra-short-term solar irradiance ...
Kalshi has emerged as a significant force. It highlights research that positions its platform as a superior tool for ...
Legacy load forecasting models are struggling with ever-more-common, unpredictable events; power-hungry AI offers a solution.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback