Iterative-Type Evaluation of PSGS Fuzzy Systems for Anytime Use

Takács, Orsolya; Várkonyi-Kóczy, Annamária R.

doi:10.1109/tim.2004.838118

Cited by 4 publications

(1 citation statement)

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“…ANYTIME PROCESSING In recourse, data, and time insufficient conditions, the so-called anytime algorithms, models, and systems [4], [5], [15] can be used advantageously. They are able to provide guaranteed response time and are flexible with respect to the available input data, time, and computational power.…”

Section: IImentioning

confidence: 99%

Anytime model regression

Várkonyi-Kóczy

Várkonyi

2012

2012 IEEE 10th International Symposium on Applied Machine Intelligence and Informatics (SAMI)

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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.

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Section: IImentioning

confidence: 99%