Classification, forecasting and decision support - invited session at KES2020

KES 2020


Artificial Intelligence



The objective of the session is the presentation of original, unpublished results on recent advances in classification, forecasting and decision sport systems. The suggested but not limited scope of the session includes the following topics:
- Classification – theory and applications
- Committees of classifiers
- Classification of biometric data
- Time series forecasting, forecasting of sequences
- Learning classification and forecasting models
- Deep learning
- Conflict resolution in classification and forecasting
- Dealing with missing and lacking data in classification and forecasting
- Dealing with dispersed knowledge in classification and forecasting
- Feature selection for classification and forecasting
- Dealing with big data in classification and forecasting
- Soft computing techniques (fuzzy sets, rough sets and other)
- Neuro, fuzzy and neuro-fuzzy models, fuzzy cognitive maps
- Statistical models, statistical reasoning
- Decision support systems (DSS) – design and implementation
- DSS architectures and algorithms (TOPSIS, AHP, other), multi-criteria decision problems
- Medical DSS, medical diagnosis, medical guidelines, medical pathways
- Financial DSS, financial forecasting