1. On advising to system operators M. Valečková, M. Kárný

2. System (with regulators) Inputs Outputs Operator Aim: advisory system as support for operators Tool: modelling of block (system + operators)

3. Example: cold rolling mill recorded hundreds of variables relevant about 40 (possibly corelated) independent inputs operator’s settings generated by system regulators required

4. Choice of model Requirements: simple respecting high-dimensional data multimodal data-based transparent construction of advice Probabilistic mixtures

5. Mixture estimation multidimensional data = samples from mixture p(x 1,x 2,..,x n ) =  i  N(  i  R i ) Estimation of unknown parameters (Bayesian approach) quick, on-line, numeriaclly stable algorithm strongly dependent on initialization

6. Result of mixture estimation joint distribution of all variables

7. Result of mixture estimation

8. How to provide an advice different operator + different “mood” = different behaviour mode of behaviour ~ component of mixture recommended component – the best quality marker

9. Simplification one component used for advising joint distribution – conditional distribution p(operator’s settings | the rest) – time dependent

10. Open problems choice of model model estimation initialization construction of advice Acknowledgement: EC Project ProdaCTool IST-1999-12058