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Bayesian Model for Evaluating Real-World Adaptation Progress of a Cyber-Physical System

Bayesian Model for Evaluating Real-World Adaptation Progress of a Cyber-Physical System
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Author(s): Arif Sari (Girne American University, Cyprus)and Joshua Chibuike Sopuru (Girne American University, Cyprus)
Copyright: 2021
Pages: 20
Source title: Artificial Intelligence Paradigms for Smart Cyber-Physical Systems
Source Author(s)/Editor(s): Ashish Kumar Luhach (The PNG University of Technology, Papua New Guinea)and Atilla Elçi (Hasan Kalyoncu University, Turkey)
DOI: 10.4018/978-1-7998-5101-1.ch015

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Abstract

Cyber-physical systems, also known as CPS, have come to stay. There is no doubt, CPS would one day outnumber humans in industries. How do we evaluate the adaptation progress of these systems considering changing environmental conditions? A failed implementation of a CPS can result to a loss. Since CPSs are designed to automate industrial activities, which are centred on the use of several technologies, collaboration with humans may sometimes be inevitable. CPSs are needed to automate several processes and thus help firms compete favourably within an industry. This chapter focuses on the adaptation of CPS in diverse work environment. Considering the ecosystem of the CPS, the authors present a Bayesian model evaluating the progress of adaptation of a CPS given some known conditions.

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