| Presentation | 2019-05-30 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, Masayoshi Hukushima, Akira Idoue, Ogawa Tetsuji, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(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) |
| Keyword(in English) | Hamiltonian Monte Carlo / State space model / Fixed shore net fishing / Fish catch forecasting |
| Paper # | PRMU2019-3 |
| Date of Issue | 2019-05-23 (PRMU) |
| Conference Information | |
| Committee | PRMU / IPSJ-CVIM |
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| Conference Date | 2019/5/30(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Shinichi Sato(NII) |
| Vice Chair | Yoshihisa Ijiri(Omron) / Toru Tamaki(Hiroshima Univ.) |
| Secretary | Yoshihisa Ijiri(NEC) / Toru Tamaki(Osaka Univ.) |
| Assistant | Go Irie(NTT) / Yoshitaka Ushiku(Univ. of Tokyo) |
| Paper Information | |
| Registration To | Technical Committee on Pattern Recognition and Media Understanding / Special Interest Group on Computer Vision and Image Media |
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| Language | JPN |
| 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 |
| 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.) |
| Date | 2019-05-30 |
| Paper # | PRMU2019-3 |
| Volume (vol) | vol.119 |
| Number (no) | PRMU-64 |
| Page | pp.pp.13-18(PRMU), |
| #Pages | 6 |
| Date of Issue | 2019-05-23 (PRMU) |