Abstract
The paper deals with the use of Support Vector Machines (SVMs) and performance comparisons with Artificial Neural Networks (ANNs) in software-based Instrument Fault Accommodation schemes. As an example, a real case study on an automotive systems is presented. The ANNs and SVMs regression capability are employed to accommodate faults that could occur on main sensors involved in the operating engine. The obtained results prove the good behaviour of both tools and similar performances have been achieved in terms of accuracy. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Capriglione, D., Marrocco, C., Molinara, M., & Tortorella, F. (2005). SVM based regression schemes for instruments fault accommodation in automotive systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3617 LNCS, pp. 1117–1124). https://doi.org/10.1007/11553595_137
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