Document Actions
Decision Making, Optimisation and Computational Intelligence
Classic and emerging optimisation methods with applications in energy systems, methodologies for multi-criteria decision support, including risk models and methodologies based on metaheuristics and evolutionary computation for optimisation and decision making. Computational intelligence based models (e.g. fuzzy systems, neural networks) for applications in energy systems.
Based on the our experience in applying methodologies to optimise decision support and our solid knowledge on classic and emerging methods of optimisation, we at the Centre for Power and Energy Systems (CPES) are able to address problems and develop methodologies and solutions in this scientific area. The following areas can be highlighted:
- Multi-criteria decision support
- Uncertainty and risk modelling
- Optimisation based on metaheuristics and evolutionary computation
- Fuzzy models for power systems
- Models based on neural networks
- Decision trees
- Support vector machines
- Data streams
- Fuzzy inference systems
- Paraconsistent logic models
- Kalman filters
- Time series
- Regression
- Kernel regression for forecasting and classification
Forgot your password?
