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Paper Abstract and Keywords
Presentation 2013-10-18 13:30
PoP: Prediction on Predictions
Hideo Hirose, Takenori Sakumura, Yuki Koyanagi (Kyushu Inst. of Tech.) R2013-64
Abstract (in Japanese) (See Japanese page) 
(in English) In observing the widely spread of patients caused by infectious diseases or the increase of the number of failures of equipments, it is crucial to predict the final number of infected patients or failures at earlier stages. To estimate the number of infected patients, the SIR model is commonly used even when the size of observed data is small. Other methods, such as the ordinary differential equation model, statistical truncated model are also useful to estimate the number of infected patients. These methods are also applicable to the increase of the number of failures.
The predicted value for the final number of patients using data until time T becomes a function (trend) of T. We here consider the use of this trend again to predict the final number of patients.
It seems that the prediction accuracy will not be increased by this method because we use the same data.
However, we may expect the better predicted values if we apply the multiple methodologies to the same data. In this paper, we show this by applying the results of the SARS case using the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) PoP / Pandemic / SIR model / ordinary differential equation model / statistical truncated model / generalized logistic distribution / BBS method /  
Reference Info. IEICE Tech. Rep., vol. 113, no. 249, R2013-64, pp. 1-6, Oct. 2013.
Paper # R2013-64 
Date of Issue 2013-10-11 (R) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
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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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee R  
Conference Date 2013-10-18 - 2013-10-18 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To R 
Conference Code 2013-10-R 
Language English (Japanese title is available) 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) PoP: Prediction on Predictions 
Sub Title (in English)  
Keyword(1) PoP  
Keyword(2) Pandemic  
Keyword(3) SIR model  
Keyword(4) ordinary differential equation model  
Keyword(5) statistical truncated model  
Keyword(6) generalized logistic distribution  
Keyword(7) BBS method  
Keyword(8)  
1st Author's Name Hideo Hirose  
1st Author's Affiliation Kyushu Institute of Technology (Kyushu Inst. of Tech.)
2nd Author's Name Takenori Sakumura  
2nd Author's Affiliation Kyushu Institute of Technology (Kyushu Inst. of Tech.)
3rd Author's Name Yuki Koyanagi  
3rd Author's Affiliation Kyushu Institute of Technology (Kyushu Inst. of Tech.)
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Speaker
Date Time 2013-10-18 13:30:00 
Presentation Time 25 
Registration for R 
Paper # IEICE-R2013-64 
Volume (vol) IEICE-113 
Number (no) no.249 
Page pp.1-6 
#Pages IEICE-6 
Date of Issue IEICE-R-2013-10-11 


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