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Estimation computational models of the cyber-physical systems functioning

Authors: Pankratova, Nataliya D.; Ptukha, Y. A.;

Estimation computational models of the cyber-physical systems functioning

Abstract

This paper reviews the use of computational models to support the functioning of cyber-physical systems (CPS) in the parallel world of the Internet of Things (IoT). Existing models, methods, techniques and their implementation in this direction are studied. The necessity of using machine learning methods due to inaccuracy, fuzziness, incompleteness of the transmitted data from sensors of physical systems is substantiated. The task is to make informed decisions in a timely manner to support the functioning of real objects of a particular cyber-physical system in real time conditions.

Keywords

cyber-physical systems; the Internet of Things; system methodology; machine learning; computer systems; sensors, киберфизические системы; интернет вещей; системная методология; машинное обучение; компьютерные системы; датчики, machine learning, Electronic computers. Computer science, system methodology, computer systems, кіберфізичні системи; інтернет речей; системна методологія; машинне навчання; комп'ютерні системи; датчики, QA75.5-76.95, cyber-physical systems, the Internet of Things, sensors

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
gold