{"created":"2025-01-19T01:30:49.893340+00:00","updated":"2025-01-19T10:59:07.066893+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230830","sets":["6504:11436:11444"]},"path":["11444"],"owner":"44499","recid":"230830","title":["水深の違いを考慮した転移学習による海水温予測モデルの提案と実装"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"33937b8f-53cf-4ad8-a2ee-84f89938729f"},"_deposit":{"id":"230830","pid":{"type":"depid","value":"230830","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"水深の違いを考慮した転移学習による海水温予測モデルの提案と実装","author_link":["622459","622461","622460"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"水深の違いを考慮した転移学習による海水温予測モデルの提案と実装"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"コンピュータと人間社会","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"名工大"},{"subitem_text_value":"名工大"},{"subitem_text_value":"名工大"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/230830/files/IPSJ-Z85-2ZH-06.pdf","label":"IPSJ-Z85-2ZH-06.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-2ZH-06.pdf","filesize":[{"value":"385.3 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"0f113fc9-1f20-4fe0-9a45-80addb2b45fd","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"三輪, 拓真"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"青山, 周平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大塚, 孝信"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"養殖業は世界的に重要な産業であり，海産物の中には大半が養殖で生産されているものもある．しかし養殖業では海水の異常水温によって品質低下やへい死などの被害が発生している．そのため機械学習を用いた海水温予測が研究されてきたが，既存の研究では予測に約9年という大量の訓練データを必要としている．そこで本研究では1年程度の少量のデータでも予測が可能な転移学習を用いた海水温予測モデルを提案した．さらに本提案モデルでは水温観測地点間の水深の違いを考慮することで予測精度向上を試みた．実験の結果，少量のデータで学習した際に，転移学習を行うことで予測精度が向上することを示した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"590","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"589","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":230830,"links":{}}