Forecast of operational data in electric energy plants using adaptive algorithm
Traditional time series methods offer models whose parameters remain constant over time. However, industrial supply and demand processes require timely decisions based on a dynamic reality. A change in configuration, turning off, or on a production line or process, modifies the problem and the varia...
- Autores:
-
Viloria, Amelec
García Guiliany, Jesús Enrique
Hernandez-P, Hugo
CABAS VASQUEZ, LUIS CARLOS
Pineda, Omar
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2020
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7726
- Acceso en línea:
- https://hdl.handle.net/11323/7726
https://doi.org/10.1007/978-981-15-3125-5_48
https://repositorio.cuc.edu.co/
- Palabra clave:
- Time series models
Estimation
Forecasts
Data analysis
Data mining
Statistical learning
Decision trees
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International