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Paper Abstract and Keywords
Presentation 2016-01-29 10:15
Analysis of Family Electricity Data Obtained by Smart Meters
Kazuki Omomo, Yuta Kobiyama, Qiangfu Zhao (Univ. Aizu) ASN2015-90
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, by using electricity data obtained by smart meters located in residential houses, we try to predict future amount of electricity. If we can predict it correctly for all families, we promise to improve the accuracy of the prediction for all over the region and to reduce the cost of electricity generation for electricity companies. As prediction methods, we investigate a method using Support Vector Regressions (SVRs) and a method using Autoregressive Integrated Moving Average (ARIMA) models. Then we compare these methods. Experimental results show that for single-person families, it is almost impossible to predict the electricity, even if we use non-linear models like SVR. For multi-person families, on the other hands, we can predict the electricity relatively well
even if we use linear model like ARIMA.
Keyword (in Japanese) (See Japanese page) 
(in English) Smart meter / Electricity consumption / Support vector regression / ARIMA model / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 437, ASN2015-90, pp. 63-68, Jan. 2016.
Paper # ASN2015-90 
Date of Issue 2016-01-21 (ASN) 
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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Conference Information
Committee MICT ASN MoNA  
Conference Date 2016-01-28 - 2016-01-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Hotel Okada 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Ambient intelligence, ICT for Medical, Healthcare and Sports, etc 
Paper Information
Registration To ASN 
Conference Code 2016-01-MICT-ASN-MoNA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Analysis of Family Electricity Data Obtained by Smart Meters 
Sub Title (in English)  
Keyword(1) Smart meter  
Keyword(2) Electricity consumption  
Keyword(3) Support vector regression  
Keyword(4) ARIMA model  
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1st Author's Name Kazuki Omomo  
1st Author's Affiliation University of Aizu (Univ. Aizu)
2nd Author's Name Yuta Kobiyama  
2nd Author's Affiliation University of Aizu (Univ. Aizu)
3rd Author's Name Qiangfu Zhao  
3rd Author's Affiliation University of Aizu (Univ. Aizu)
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Speaker
Date Time 2016-01-29 10:15:00 
Presentation Time 25 
Registration for ASN 
Paper # IEICE-ASN2015-90 
Volume (vol) IEICE-115 
Number (no) no.437 
Page pp.63-68 
#Pages IEICE-6 
Date of Issue IEICE-ASN-2016-01-21 


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