Paper Abstract and Keywords |
Presentation |
2017-03-10 09:10
Data Mining and Private Information Detection Method using Power Demand Yoshida Masahiro, Imanishi Tomoya, Nishi Hiroaki (Keio Univ.) CPSY2016-143 DC2016-89 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Recently, detailed power demand information of the building is being aggregated, accompanied by the spread of smart meters. Continuous spread of smart meter will aggregate large amount of data from area in several conditions. In order to utilize these data effectively, feature extraction method that is generic, and law computational cost is required. Therefore, the feature value extraction method for power demand information is proposed in this report. Furthermore, we estimate family structure and floor space from the extracted feature value, and evaluate the proposal method through its estimation accuracy, computational cost, and generality. As the result, we have managed to improve the estimation accuracy compared to the existing method. We have also verified its’ generality by adopting the proposal method to data aggregated from different conditions. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Smart meter / Feature extraction / Machine learning / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 116, no. 511, DC2016-89, pp. 285-290, March 2017. |
Paper # |
DC2016-89 |
Date of Issue |
2017-03-02 (CPSY, DC) |
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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CPSY2016-143 DC2016-89 |
Conference Information |
Committee |
CPSY DC IPSJ-SLDM IPSJ-EMB IPSJ-ARC |
Conference Date |
2017-03-09 - 2017-03-10 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Kumejima Island |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
ETNET20167 |
Paper Information |
Registration To |
DC |
Conference Code |
2017-03-CPSY-DC-SLDM-EMB-ARC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Data Mining and Private Information Detection Method using Power Demand |
Sub Title (in English) |
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Smart meter |
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Feature extraction |
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Machine learning |
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1st Author's Name |
Yoshida Masahiro |
1st Author's Affiliation |
Keio University (Keio Univ.) |
2nd Author's Name |
Imanishi Tomoya |
2nd Author's Affiliation |
Keio University (Keio Univ.) |
3rd Author's Name |
Nishi Hiroaki |
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Keio University (Keio Univ.) |
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Speaker |
Author-1 |
Date Time |
2017-03-10 09:10:00 |
Presentation Time |
20 minutes |
Registration for |
DC |
Paper # |
CPSY2016-143, DC2016-89 |
Volume (vol) |
vol.116 |
Number (no) |
no.510(CPSY), no.511(DC) |
Page |
pp.285-290 |
#Pages |
6 |
Date of Issue |
2017-03-02 (CPSY, DC) |
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