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.
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