SVM Based Regression Schemes for Instruments Fault Accommodation in Automotive Systems

2005 JOURNAL IRIS

Authors: a cura di F. ROLI, S. VITULANO, CAPRIGLIONE, Domenico, MARROCCO, Claudio, MOLINARA, Mario, TORTORELLA, Francesco

Venue: Lecture Notes in Computer Science 3617

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.

BibTeX

@article{acuradifrolisvitulano2005svm,
  title={SVM Based Regression Schemes for Instruments Fault Accommodation in Automotive Systems},
  author={a cura di F. ROLI, S. VITULANO and CAPRIGLIONE, Domenico and MARROCCO, Claudio and MOLINARA, Mario and TORTORELLA, Francesco},
  journal={Lecture Notes in Computer Science 3617},
  year={2005},
  doi={10.1007/11553595_137}
}

Links

Sorgente istituzionale: IRIS/CINECA

Aggiornato: 23/09/2026 21:38