Machine Learning for Hydropower Scheduling: State of the Art and Future Research Directions.
Chiara BordinHans Ivar SkjelbredJiehong KongZhirong YangPublished in: KES (2020)
Keyphrases
- machine learning
- production planning
- learning systems
- scheduling problem
- machine learning methods
- artificial intelligence
- active learning
- text mining
- round robin
- multistage
- learning algorithm
- scheduling algorithm
- machine learning algorithms
- computer vision
- resource allocation
- explanation based learning
- pattern recognition
- real time
- dynamic scheduling
- inductive learning
- machine learning and data mining
- genetic algorithm
- model selection
- knowledge acquisition
- supervised learning
- flexible manufacturing systems
- parallel processors
- preventive maintenance
- supervised machine learning
- learning tasks
- transfer learning
- computational intelligence
- natural language processing
- information extraction
- computer science
- real world