Talks and Poster Presentations (with Proceedings-Entry):
M. Killian, S. Grosswindhager, M. Kozek, B. Mayer:
"Pre-processing of Partition Data for Enhancement of LOLIMOT";
Talk: 8th EUROSIM Congress on Modelling and Simulation,
Cardiff, Wales;
2013-09-10
- 2013-09-13; in: "Proceedings of the 8th EUROSIM Congress on Modelling and Simulation 2013",
(2013),
ISBN: 978-0-7695-5073-2;
5 pages.
English abstract:
The Local Linear Model Tree (LOLIMOT) algorithm
is a versatile tool for black-box identification of nonlinear
complex systems with a set of local linear models. In this
work two methods for pre-processing of the partition data for
this algorithm are presented. These methods aim at reducing
the number of LLMs while improving the global model fit.
The proposed methods are a (linear or nonlinear) principal
component analysis and a rotational transformation of the
input space. Both methods aim at mitigating the limitations of
the axis-orthogonal splits in the partition space that LOLIMOT
performs. The application to real data from industrial processes
and the e ectiveness is demonstrated on a grate-fired biomass
plant and the thermal model of a large o ce building.
Keywords:
LOLIMOT; system identification; modelling tools; simulation.
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1109/EUROSIM.2013.56
Related Projects:
Project Head Martin Kozek:
Robuste Prädiktive Regelstrategien zur Optimierung des Energieeinsatzes in Gebäuden
Created from the Publication Database of the Vienna University of Technology.