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Paper Abstract and Keywords
Presentation 2024-02-29 17:10
Comparison of OSS Reliability Assessment Methods Based on Deep Learning Considering the Wiener and Jump Diffusion Processes
Yoshinobu Tamura, Shoichiro Miyamoto, Lei Zhou (Yamaguchi Univ.), Shigeru Yamada (Tottori Univ.) R2023-63
Abstract (in Japanese) (See Japanese page) 
(in English) In many research fields, the methods based on deep learning have been proposed. In this paper, we propose the method of reliability assessment based on the deep learning by using the fault big data obtained from the bug tracking system. In particular, various noisy data are included on the fault big data. In this paper, we focus on the fault modification time data as the objective variable. We discuss the prediction accuracy of deep learning by using the data preprocessing based on the Wiener process and jump diffusion one.
Keyword (in Japanese) (See Japanese page) 
(in English) Open Source Software / Data Preprocessing / Wiener Process / Jump Diffusion Process / Big Data / Deep Learning / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 399, R2023-63, pp. 46-51, Feb. 2024.
Paper # R2023-63 
Date of Issue 2024-02-22 (R) 
ISSN 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)
Download PDF R2023-63

Conference Information
Committee R  
Conference Date 2024-02-29 - 2024-02-29 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English) Reliability of Electromechanical Devices, Reliability of Computer System, Reliability General 
Paper Information
Registration To R 
Conference Code 2024-02-R 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Comparison of OSS Reliability Assessment Methods Based on Deep Learning Considering the Wiener and Jump Diffusion Processes 
Sub Title (in English)  
Keyword(1) Open Source Software  
Keyword(2) Data Preprocessing  
Keyword(3) Wiener Process  
Keyword(4) Jump Diffusion Process  
Keyword(5) Big Data  
Keyword(6) Deep Learning  
Keyword(7)  
Keyword(8)  
1st Author's Name Yoshinobu Tamura  
1st Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
2nd Author's Name Shoichiro Miyamoto  
2nd Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
3rd Author's Name Lei Zhou  
3rd Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
4th Author's Name Shigeru Yamada  
4th Author's Affiliation Tottori University (Tottori Univ.)
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Speaker Author-1 
Date Time 2024-02-29 17:10:00 
Presentation Time 25 minutes 
Registration for R 
Paper # R2023-63 
Volume (vol) vol.123 
Number (no) no.399 
Page pp.46-51 
#Pages 6 
Date of Issue 2024-02-22 (R) 

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