Title
Virtual sensors for emissions of a Diesel engine produced by evolutionary system identification
Date Issued
01 December 2009
Access level
metadata only access
Resource Type
conference paper
Author(s)
Johannes Kepler University Linz
Abstract
In this paper we discuss the generation of models for emissions of a Diesel engine, produced by genetic programming based evolutionary system identification: Models for the formation of NOx and particulate matter emissions are identified and analyzed. We compare these models to models designed by experts applying variables section and the identification of local polynomial models; analyzing the results summarized in the empirical part of this paper we see that the use of enhanced genetic programming yields models for emissions that are valid not only in certain parts of the parameter space but can be used as global virtual sensors. © 2009 Springer-Verlag Berlin Heidelberg.
Start page
657
End page
664
Volume
5717 LNCS
Language
English
OCDE Knowledge area
Biotecnología industrial
Mecánica aplicada
Subjects
Scopus EID
2-s2.0-78651227589
Resource of which it is part
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN of the container
03029743
ISBN of the container
978-364204771-8
Conference
12th International Conference on Computer Aided Systems Theory, EUROCAST 2009
Sponsor(s)
The work described in this paper was done within the Translational Research Program project L284-N04 “GP-Based Techniques for the Design of Virtual Sensors” sponsored by the Austrian Science Fund (FWF). The involved research organizations are the Heuristic and Evolutionary Algorithms Laboratory at the Upper Austria University of Applied Sciences, Faculty of Informatics, Communications and Media, and the Linz Center of Mechatronics.
Sources of information:
Directorio de Producción Científica
Scopus