Andrea Schrems, Hajrudin Efendic, Kurt Pichler,
"Selection of Physically Interpretable Data Driven Model Structures to Analyze Industrial Processes"
: Proceedings of the 11th WSEAS International Conference on Automatic Control, Modelling and Simulation, 6-2009
Original Titel:
Selection of Physically Interpretable Data Driven Model Structures to Analyze Industrial Processes
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the 11th WSEAS International Conference on Automatic Control, Modelling and Simulation
Original Kurzfassung:
This work presents a black-box input selection approach to reveal causal dependencies between process variables of complex industrial systems. This allows data based modeling with physically interpretable model structure.
For this purpose a method is used which combines statistical and analytical approaches to find causal relations between measured data, detection of control loops and the interaction of conditional system behavior respectively. The quality of such models remains in comparison to a common statistical approach unchanged high. The benefit of this input identification approach is an improved insight in complex processes for modeling purposes and their applications.
Sprache der Kurzfassung:
Englisch
Erscheinungsmonat:
6
Erscheinungsjahr:
2009
Anzahl der Seiten:
7
Notiz zur Publikation:
Proceedings of the 11th WSEAS International Conference on Automatic Control, Modelling and Simulation, May 30 - June 1, 2009, Istanbul, Turkey