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https://www.researchgate.net/profile/Ajith_Kumar_Parlikad/publication/259621540_A_Bayesian_decision_support_system_for_vehicle_component_recovery/links/54230f1d0cf290c9e3ae2632/A-Bayesian-decision-support-system-for-vehicle-component-recovery.pdf
A Bayesian decision support system for vehicle component recovery 417 problem domain which will help us in developing a model of the process to assist decision-making.
https://www.researchgate.net/publication/259621540_A_Bayesian_decision_support_system_for_vehicle_component_recovery
A Bayesian decision support system for vehicle component recovery 421. with returned vehicles, effective recovery of value requires an automated means to. capture, store and retrieve extensive information about the identity and condition of. constituent components at the time of return (Parlikad and McFarlane, 2007).
https://www.academia.edu/1877506/A_Bayesian_decision_support_system_for_vehicle_component_recovery
A Bayesian decision support system for vehicle component recovery
https://www.deepdyve.com/lp/inderscience-publishers/a-bayesian-decision-support-system-for-vehicle-component-recovery-mb4SkDUkze
Jan 01, 2009 · A Bayesian decision support system for vehicle component recovery Parlikad, Ajith Kumar ; McFarlane, Duncan 2009-01-01 00:00:00 This paper presents a decision support system (DSS) whose core is based on Bayes' networks and influence diagrams that helps remanufacturers to choose the best product recovery option on the basis of the information provided by emerging …
https://www.inderscience.com/info/inarticletoc.php?jcode=ijsm&year=2009&vol=1&issue=4
A Bayesian decision support system for vehicle component recovery Ajith Kumar Parlikad, Duncan McFarlane DOI: 10.1504/IJSM.2009.031362: 437-449: Characteristics of the automotive remanufacturing enterprise with an economic and environmental evaluation of alternator products Hyung-Ju Kim, Steve Skerlos, Semih Severengiz, Guenther Seliger
https://link.springer.com/article/10.1007/s10115-019-01419-1
The experiment results show that the service recovery decision support system can have the high performance of customer recognition. Meanwhile, customer emotion can be a clue to enable businesses to make the right service decisions in service recovery.Author: Yen-Hao Hsieh, Szu-Chieh Chen
http://www3.eng.cam.ac.uk/research_db/publications/aknp2
Parlikad, AK and McFarlane, D (2009) A Bayesian decision support system for vehicle component recovery. International Journal of Sustainable Manufacturing, 1. pp. 415-436. ISSN 1742-7223. Ouertani, MZ and Parlikad, AKN and McFarlane, DC (2008) Towards an approach to select an asset information management strategy.
https://arxiv.org/pdf/1211.2126
application of a Medical Decision Support System (MDSS). This system has to make dynamic decision on temporal data. We use dynamic Bayesian network (DBN) to model this dynamic process. It is a temporal reasoning within a real-time environment; we are interested in the Dynamic Decision Support Systems in healthcare domain (MDDSS).Cited by: 16
https://store.samhsa.gov/system/files/sma16-4993.pdf
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