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Paper Abstract and Keywords
Presentation 2014-03-07 13:00
Decision Support of Observation Areas by Bayesian Network
Megumi Sawada, Atsuo Ozaki, Shusuke Watanabe (Mitsubishi Electric) MSS2013-90
Abstract (in Japanese) (See Japanese page) 
(in English) Bayesian network is desired as an effective approach for the decision support of the observation areas in a situational awareness (medical diagnosis, intruder surveillance and so on). In each observation area, Occurrence or non-occurrence of the events related to the target of situation awareness (disease, intruder’s purpose and so on) changes with time. However, Bayesian network cannot handle the probability event that changes with time. To solve this problem, we proposed the method that introduces the time concept to Bayesian network for the decision support of the observation areas. The proposed method extends Bayesian network to estimate the temporal state (for example, inactive, active and complete) about each phase of the target scenario. Specifically, the time progression of the scenario is estimated by changing the probability value of the temporal state of each phase based on “the temporal state of the before and after phases” and “the acquisition time and the content of observation information”. This estimation result would be utilized to recommend the phase of the active state as the target that should be observed preferentially.
Keyword (in Japanese) (See Japanese page) 
(in English) Bayesian Network / Observation Planning / Situational Awareness / Decision Support / / / /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 466, MSS2013-90, pp. 83-87, March 2014.
Paper # MSS2013-90 
Date of Issue 2014-02-27 (MSS) 
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)
Download PDF MSS2013-90

Conference Information
Committee MSS  
Conference Date 2014-03-06 - 2014-03-07 
Place (in Japanese) (See Japanese page) 
Place (in English) Ehime Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MSS 
Conference Code 2014-03-MSS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Decision Support of Observation Areas by Bayesian Network 
Sub Title (in English)  
Keyword(1) Bayesian Network  
Keyword(2) Observation Planning  
Keyword(3) Situational Awareness  
Keyword(4) Decision Support  
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1st Author's Name Megumi Sawada  
1st Author's Affiliation Mitsubishi Electric Corporation (Mitsubishi Electric)
2nd Author's Name Atsuo Ozaki  
2nd Author's Affiliation Mitsubishi Electric Corporation (Mitsubishi Electric)
3rd Author's Name Shusuke Watanabe  
3rd Author's Affiliation Mitsubishi Electric Corporation (Mitsubishi Electric)
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Speaker Author-1 
Date Time 2014-03-07 13:00:00 
Presentation Time 25 minutes 
Registration for MSS 
Paper # MSS2013-90 
Volume (vol) vol.113 
Number (no) no.466 
Page pp.83-87 
#Pages 5 
Date of Issue 2014-02-27 (MSS) 

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