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Ultima descărcare din IBN: 2019-05-03 02:50 |
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519.217:004.891 (2) |
Теория вероятностей и математическая статистика (80) |
Искусственный интеллект (303) |
SM ISO690:2012 BOUAMRANE, Karim, DJEBBAR, Amel, ATMANI, Baghdad. An Approach of Diagnosis Based On The Hidden Markov Chains Model.. In: Computer Science Journal of Moldova, 2008, nr. 2(47), pp. 256-268. ISSN 1561-4042. |
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Computer Science Journal of Moldova | ||||||
Numărul 2(47) / 2008 / ISSN 1561-4042 /ISSNe 2587-4330 | ||||||
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CZU: 519.217:004.891 | ||||||
Pag. 256-268 | ||||||
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Rezumat | ||||||
Diagnosis is a key element in industrial system maintenance process performance. A diagnosis tool is proposed allowing the maintenance operators capitalizing on the knowledge of their trade and subdividing it for better performance improvement and intervention effectiveness within the maintenance process service. The Tool is based on the Markov Chain Model and more precisely the Hidden Markov Chains (НМС) which has the system failures determination advantage, taking into account the causal relations, stochastic context modeling of their dynamics and providing a relevant diagnosis help by their ability of dubious information use. Since the FMEA method is a well adapted artificial intelligence field, the modeling with Markov Chains is carried out with its assistance. Recently, a dynamic programming recursive algorithm, called 'Viterbi Algorithm', is being used in the Hidden Markov Chains field. This algorithm provides as input to the HMC a set of system observed effects and generates at exit the various causes having caused the loss from one or several system functions. |
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Cuvinte-cheie Diagnosis, Markov Chain, Hidden Markov Chain (HMC), FMEA, Viterbi Algorithm |
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