{"created":"2025-01-19T01:29:23.003461+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229928","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229928","title":["Transformerモデルを用いたAISデータから船舶軌跡の予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"eb993831-51a0-4605-a622-42316331f29f"},"_deposit":{"id":"229928","pid":{"type":"depid","value":"229928","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Transformerモデルを用いたAISデータから船舶軌跡の予測","author_link":["618551"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Transformerモデルを用いたAISデータから船舶軌跡の予測"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","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":"防衛大"}]},"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/229928/files/IPSJ-Z85-6Q-07.pdf","label":"IPSJ-Z85-6Q-07.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-6Q-07.pdf","filesize":[{"value":"460.6 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"26ae16a4-602c-4da5-89be-ea10b9a9cc94","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":"タインコン, ダン"}],"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":"　海上交通の発展に伴い、将来の船舶の位置を予測することは、多くの海上監視・海上状況認識(MSA)に不可欠である。例えば、交通管制、経路計画、捜索などのタスクに、船舶位置の正確な予測があれば非常に役立つ。　2017年に登場したTransformerという深層学習モデルが、異常検知、自然言語処理などにおいて、最先端モデル(state-of-art model)となっている。Transformerは時系列予測にも用いることができるが、船舶の位置を予測する問題にはあまり使われていない。　本研究では、いくつかの先行研究を活用しながら、船舶の軌跡の予測問題を解決できる新しいモデルを作成する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"262","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"261","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"links":{},"id":229928,"updated":"2025-01-19T11:21:31.831414+00:00"}