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Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models : Theory and Applications

Deep, Kusum and Jain, Madhu and Salhi, Said, eds. (2019) Performance Prediction and Analytics of Fuzzy, Reliability and Queuing Models : Theory and Applications. Asset Analytics . Springer, Singapore, Singapore, 250 pp. ISBN 978-981-1308-56-7. E-ISBN 978-981-1308-57-4. (doi:10.1007/978-981-13-0857-4) (KAR id:68436)

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Official URL
http://dx.doi.org/10.1007/978-981-13-0857-4.

Abstract

This book presents the latest developments and breakthroughs in fuzzy theory and

performance prediction of queuing and reliability models by using the stochastic modeling and

optimization theory. The main focus is on analytics that use fuzzy logic, queuing and reliability

theory for the performance prediction and optimal design of real-time engineering systems

including call centers, telecommunication, manufacturing, service organizations, etc. For the dayto-

day as well as industrial queuing situations and reliability prediction of machining parts

embedded in computer, communication and manufacturing systems, the book assesses various

measures of performance and effectiveness that can provide valuable insights and help arrive

at the best decisions with regard to service and engineering systems. In twenty chapters, the

book presents both theoretical developments and applications of the fuzzy logic, reliability and

queuing models in a diverse range of scenarios. The topics discussed will be of interest to

researchers, educators and undergraduate students in the fields of Engineering, Business

Management, and the Mathematical Sciences.

Item Type: Edited book
DOI/Identification number: 10.1007/978-981-13-0857-4
Uncontrolled keywords: analytics, fuzzy logic, reliability, performance, prediction, queueing
Subjects: H Social Sciences > H Social Sciences (General)
Divisions: Central Services > Research and Innovation Services
Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems
Depositing User: Said Salhi
Date Deposited: 26 Jul 2018 10:26 UTC
Last Modified: 06 Oct 2021 11:04 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/68436 (The current URI for this page, for reference purposes)
Salhi, Said: https://orcid.org/0000-0002-3384-5240
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