Anytime model regression

A. Várkonyi-Kóczy, Térez A. Várkonyi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Regression-type techniques are widely used for system modeling and characterization. In many of the cases the characterizations are to be performed on-line to be able to support control actions and other decisions which are necessary for the operation. In autonomous time critical and embedded systems there are further requirements to be met. Robustness and flexibility in respect to the actual state of the system and its environment belong to this group because the available time, resource, and data conditions have a direct effect on the feasibility and quality of the modeling or characterization. An important expectation concerning the processing is to ensure continuous operation and to offer "immediate" results in certain (e.g. crisis) situations. Anytime tools are serious candidates to measure up to such purposes because they can always provide some kind of results even if abrupt changes, temporal shortage of computational power, and/or loss of some data occur in the system/environment. In this paper an anytime model regression technique is presented which can advantageously contribute to the modeling/characterization tasks.

Original languageEnglish
Title of host publicationIEEE 10th Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012 - Proceedings
Pages253-258
Number of pages6
DOIs
Publication statusPublished - 2012
Event10th IEEE Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012 - Herl'any, Slovakia
Duration: Jan 26 2012Jan 28 2012

Other

Other10th IEEE Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012
CountrySlovakia
CityHerl'any
Period1/26/121/28/12

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Embedded systems
Processing

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction

Cite this

Várkonyi-Kóczy, A., & Várkonyi, T. A. (2012). Anytime model regression. In IEEE 10th Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012 - Proceedings (pp. 253-258). [6208968] https://doi.org/10.1109/SAMI.2012.6208968

Anytime model regression. / Várkonyi-Kóczy, A.; Várkonyi, Térez A.

IEEE 10th Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012 - Proceedings. 2012. p. 253-258 6208968.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Várkonyi-Kóczy, A & Várkonyi, TA 2012, Anytime model regression. in IEEE 10th Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012 - Proceedings., 6208968, pp. 253-258, 10th IEEE Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012, Herl'any, Slovakia, 1/26/12. https://doi.org/10.1109/SAMI.2012.6208968
Várkonyi-Kóczy A, Várkonyi TA. Anytime model regression. In IEEE 10th Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012 - Proceedings. 2012. p. 253-258. 6208968 https://doi.org/10.1109/SAMI.2012.6208968
Várkonyi-Kóczy, A. ; Várkonyi, Térez A. / Anytime model regression. IEEE 10th Jubilee International Symposium on Applied Machine Intelligence and Informatics, SAMI 2012 - Proceedings. 2012. pp. 253-258
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