National Academies of Sciences%2c Engineering%2c and Medicine

Forecasting Costs for Preserving, Archiving, and Promoting Access to Biomedical Data

National Academies' staff and study committee members will give a summary of site visits to San Diego, CA; Washington, DC; Boston, MA; and Seattle, WA. This site visit will explore data needs, ...
Nature

A novel reinforcement learning-based approach for short-term load and price forecasting in energy markets

In the last decade, one of the most important issues raised in the field of smart grids is electricity market forecasting. Today, the electricity market is not only faced with the provision of the ...
Nature

Mid-term power load forecasting using an ensemble deep learning model with BKA and CWGAN-GP enhancements

Electric load forecasting serves as a crucial decision-making foundation for the operation of power systems, offering important guidance for system scheduling optimization, cost reduction, and ...
T&D

Advancing Long-Term Forecasting for Tomorrow’s Grid

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 ...
Becker's Hospital Review

How can predictive analytics support labor cost forecasting?

While not as mature as its use in other areas, health systems across the U.S. are beginning to adopt predictive analytics tools for labor cost forecasting. Many organizations have automated ...
National Academies of Sciences%2c Engineering%2c and Medicine

Forecasting Costs for Preserving, Archiving, and Promoting Access to Biomedical Data

This study will develop and demonstrate a framework for forecasting long-term costs for preserving, archiving, and accessing various types of biomedical data and estimating potential future benefits ...