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| Presentation | 2022-01-18 11:35 Evaluation on Prediction Method for Missing Probability of Sensor Value based on Hierarchical Structure of Missing Value Norifumi Hirata, Osamu Maeshima, Kiyohito Yoshihara (KDDI Research)  IN2021-25 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Collecting sensor data via networks is important for IoT (Internet of Things) services.However, sensors sometimes have missing values by equipment failures, network failure, etc.It is possible to take actions against missing value by predicting a missing probability.For example, we can take a bid in an electricity power market except failed generators by predicting missing probability.In this paper, we propose and evaluate a prediction method for missing probability of sensor data hierarchical structure of missing value.As a result of the evaluation, the proposed method could reduce the prediction error of missing probability from 10.75% to 7.71% compared to a baseline method. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | time-series prediction / missing value / hierarchical structure / sensor value / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 324, IN2021-25, pp. 7-12, Jan. 2022. | |
| Paper # | IN2021-25 | |
| Date of Issue | 2022-01-11 (IN) | |
| 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 | IN2021-25 |
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| Conference Information | |
| Committee | IN |
| Conference Date | 2022-01-18 - 2022-01-18 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Contents Distribution, Social Networking Services, Data Analytics and Processing Platform, Big data, etc. |
| Paper Information | |
| Registration To | IN |
| Conference Code | 2022-01-IN |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Evaluation on Prediction Method for Missing Probability of Sensor Value based on Hierarchical Structure of Missing Value |
| Sub Title (in English) | |
| Keyword(1) | time-series prediction |
| Keyword(2) | missing value |
| Keyword(3) | hierarchical structure |
| Keyword(4) | sensor value |
| Keyword(5) | |
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| Keyword(8) | |
| 1st Author's Name | Norifumi Hirata |
| 1st Author's Affiliation | KDDI Research, Inc (KDDI Research) |
| 2nd Author's Name | Osamu Maeshima |
| 2nd Author's Affiliation | KDDI Research, Inc (KDDI Research) |
| 3rd Author's Name | Kiyohito Yoshihara |
| 3rd Author's Affiliation | KDDI Research, Inc (KDDI Research) |
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| Speaker | Author-1 |
| Date Time | 2022-01-18 11:35:00 |
| Presentation Time | 25 minutes |
| Registration for | IN |
| Paper # | IN2021-25 |
| Volume (vol) | vol.121 |
| Number (no) | no.324 |
| Page | pp.7-12 |
| #Pages | 6 |
| Date of Issue | 2022-01-11 (IN) |
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