Demo Data from EDBT 2026 / reviewers in the wild / expert
George Gross
dblp:64/3662
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2009
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Energy systems and smart grids · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Energy systems and smart grids
energy management |
0.0 | 1 | 1987 | Short-term load forecasting · Proc. IEEE 1987 |
Energy systems and smart grids
load forecasting |
0.0 | 1 | 1987 | Short-term load forecasting · Proc. IEEE 1987 |
Energy systems and smart grids › load forecasting
short-term load forecasting |
0.0 | 1 | 1987 | Short-term load forecasting · Proc. IEEE 1987 |
Energy systems and smart grids › power system modeling
load modeling |
0.0 | 1 | 1987 | Short-term load forecasting · Proc. IEEE 1987 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2009 | An incentive-based mechanism for transmission asset investment
Javier Contreras, George Gross, José Manuel Arroyo, José Ignacio Muñoz |
Decis. Support Syst. | 2 |
| 1987 | Short-term load forecastingabstractThis paper discusses the state of the art in short-term load forecasting (STLF), that is, the prediction of the system load over an interval ranging from one hour to one week. The paper reviews the important role of STLF in the on-line scheduling and security functions of an energy management system (EMS). It then discusses the nature of the load and the different factors influencing its behavior. A detailed classification of the types of load modeling and forecasting techniques is presented. Whenever appropriate, the classification is accompanied by recommendations and by references to the literature which support or expand the discussion. The paper also presents a lengthy discussion of practical aspects for the development and usage of STLF models and packages. The annotated bibliography offers a representative selection of the principal publications in the STLF area. George Gross, Francisco D. Galiana |
Proc. IEEE | 1 |