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| Presentation | 2019-05-30 11:20 Daily Fish Catch Forecasting For Fixed Shore Net Fishing Using State Space Model Describing Probabilistic Behavior of Fish Inside Net Yuya Kokaki, Naohiro Tawara, Tetsunori Kobayashi, Kazuo Hashimoto (Waseda Univ.), Masayoshi Hukushima, Akira Idoue (KDDI Research), Ogawa Tetsuji (Waseda Univ.)  PRMU2019-3 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | A state space model that incorporates knowledge on fixed shore net fishing was developed and suc- cessfully applied to daily fish catch forecasting. Accurate daily fish catch prediction can support fishery workers with their decision-making and efficient operation. The present study attempts to develop a fish catch forecasting method using a state space model that describes probabilistic behaviors of fish inside the net. In this method, the parameter estimation and forecasting are sequentially carried out using Hamiltonian Monte Carlo method. The experimental comparisons conducted using actual fish catch data and public meteorological data demonstrated that the developed forecasting system suitable for fixed shore net fishing reduced significant prediction errors over the systems using legacy state space models. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Hamiltonian Monte Carlo / State space model / Fixed shore net fishing / Fish catch forecasting / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 64, PRMU2019-3, pp. 13-18, May 2019. | |
| Paper # | PRMU2019-3 | |
| Date of Issue | 2019-05-23 (PRMU) | |
| 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 | PRMU2019-3 |
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| Conference Information | |
| Committee | PRMU IPSJ-CVIM |
| Conference Date | 2019-05-30 - 2019-05-31 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | PRMU |
| Conference Code | 2019-05-PRMU-CVIM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Daily Fish Catch Forecasting For Fixed Shore Net Fishing Using State Space Model Describing Probabilistic Behavior of Fish Inside Net |
| Sub Title (in English) | |
| Keyword(1) | Hamiltonian Monte Carlo |
| Keyword(2) | State space model |
| Keyword(3) | Fixed shore net fishing |
| Keyword(4) | Fish catch forecasting |
| Keyword(5) | |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Yuya Kokaki |
| 1st Author's Affiliation | Waseda University (Waseda Univ.) |
| 2nd Author's Name | Naohiro Tawara |
| 2nd Author's Affiliation | Waseda University (Waseda Univ.) |
| 3rd Author's Name | Tetsunori Kobayashi |
| 3rd Author's Affiliation | Waseda University (Waseda Univ.) |
| 4th Author's Name | Kazuo Hashimoto |
| 4th Author's Affiliation | Waseda University (Waseda Univ.) |
| 5th Author's Name | Masayoshi Hukushima |
| 5th Author's Affiliation | KDDI Research, Inc. (KDDI Research) |
| 6th Author's Name | Akira Idoue |
| 6th Author's Affiliation | KDDI Research, Inc. (KDDI Research) |
| 7th Author's Name | Ogawa Tetsuji |
| 7th Author's Affiliation | Waseda University (Waseda Univ.) |
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| Speaker | Author-1 |
| Date Time | 2019-05-30 11:20:00 |
| Presentation Time | 15 minutes |
| Registration for | PRMU |
| Paper # | PRMU2019-3 |
| Volume (vol) | vol.119 |
| Number (no) | no.64 |
| Page | pp.13-18 |
| #Pages | 6 |
| Date of Issue | 2019-05-23 (PRMU) |
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