A survey on AI-based scheduling models, optimization and prediction for hydropower generation : variants, challenges, and future directions
Yoan Villeneuve, Sara Séguin, Abdellah Chehr
| Year of publication: |
[2022]
|
|---|---|
| Authors: | Villeneuve, Yoan ; Séguin, Sara ; Chehri, Abdellah |
| Publisher: |
Montréal (Québec), Canada : GERAD, HÉC Montréal |
| Subject: | Hydropower | hydropower scheduling | machine learning | optimization | stochastic programming | linear regression | random forest | reinforcement learning | Deep Neural Networks | Wasserkraft | Neuronale Netze | Neural networks | Künstliche Intelligenz | Artificial intelligence | Theorie | Theory | Scheduling-Verfahren | Scheduling problem | Mathematische Optimierung | Mathematical programming | Stochastischer Prozess | Stochastic process | Lernprozess | Learning process | Algorithmus | Algorithm | Prognoseverfahren | Forecasting model |
freely available
| Extent: | 1 Online-Ressource (circa 28 Seiten) Illustrationen |
|---|---|
| Series: | Les cahiers du GERAD. - Montréal (Québec), Canada : GERAD, HÉC Montréal, ZDB-ID 3026340-2. - Vol. G-2022, 52 (Decembre 2022) |
| Type of publication: | Book / Working Paper |
| Type of publication (narrower categories): | Graue Literatur ; Non-commercial literature ; Arbeitspapier ; Working Paper |
| Language: | English |
| Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10013502350