Paper Abstract and Keywords |
Presentation |
2019-11-28 16:25
Reliability Methodologies for Degradation Predictions Based on Hierarchical Bayesian Modeling and Machine Learning Toru Kaise, Toyohiko Egami (Univ. of Hyogo) R2019-49 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Degradation processes are significant for making values of reliability.
Particularly, it is known that stochastic models are useful for representations of the degradation paths. In this paper, a hierarchical Bayesian VG (Variances Gamma) model is proposed for a representation of the degradation phenomenon, moreover, the real option method based on a simulation is applied to the reliability evaluation using the model with machine learning methods. In particular, the hierarchical Bayesian model is constructed in a state space model with an observation equation, and the Boltzmann machine is applied. It is also shown that the Bayesian estimation for the degradation analysis is handled based on MCMC (Markov Chain Monte Carlo) methodology and a method for comparisons of the model based on the information criterion EIC is proposed. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Degradation Process / Hierarchical Bayes / EIC / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 315, R2019-49, pp. 35-38, Nov. 2019. |
Paper # |
R2019-49 |
Date of Issue |
2019-11-21 (R) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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R2019-49 |
Conference Information |
Committee |
R |
Conference Date |
2019-11-28 - 2019-11-28 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Central Electric Club |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
Reliability of semiconductor and electronic devices, Reliability general |
Paper Information |
Registration To |
R |
Conference Code |
2019-11-R |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Reliability Methodologies for Degradation Predictions Based on Hierarchical Bayesian Modeling and Machine Learning |
Sub Title (in English) |
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Degradation Process |
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Hierarchical Bayes |
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EIC |
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1st Author's Name |
Toru Kaise |
1st Author's Affiliation |
University of Hyogo (Univ. of Hyogo) |
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Toyohiko Egami |
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University of Hyogo (Univ. of Hyogo) |
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Speaker |
Author-1 |
Date Time |
2019-11-28 16:25:00 |
Presentation Time |
25 minutes |
Registration for |
R |
Paper # |
R2019-49 |
Volume (vol) |
vol.119 |
Number (no) |
no.315 |
Page |
pp.35-38 |
#Pages |
4 |
Date of Issue |
2019-11-21 (R) |
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