The accuracy of weather forecasts produced by AI models beat meteorologists’ contemporary methods. But how they work is a bit ...
Traditional long-term forecasting models are no longer sufficient as electrification, DER growth, EV adoption, extreme weather events and new large loads introduce unprecedented complexity. The future ...
To successfully enter an international market takes far more than instinct. It demands time, disciplined research, and a strong understanding of the economic, competitive, and consumer forces shaping ...
People are now betting on everything. Prediction markets are amplifying those signals. The timing of the U.S. government shutdown. The likelihood of Taylor Swift canceling a tour date. The exact day ...
This project provides a modern, well-structured implementation of hierarchical time series forecasting methods. It supports various forecasting algorithms (ARIMA, Prophet, LSTM) and reconciliation ...
1 China Southern Power Grid Guizhou Power Supply Co., Ltd., Guiyang, Guizhou, China 2 Dongfang Electronics Co., Ltd., Yantai, Shandong, China Introduction: With increasing uncertainties on both the ...
A new study by Shanghai Jiao Tong University and SII Generative AI Research Lab (GAIR) shows that training large language models (LLMs) for complex, autonomous tasks does not require massive datasets.
In forecasting economic time series, statistical models often need to be complemented with a process to impose various constraints in a smooth manner. Systematically imposing constraints and retaining ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results