{"created":"2025-01-19T01:29:40.790271+00:00","updated":"2025-01-19T11:17:08.143824+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230113","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"230113","title":["Transformerを用いたCOVID-19の感染者数の推移予測におけるノイズ付加の効果分析"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"2caf3934-8950-43a0-ad3d-f3993d49788c"},"_deposit":{"id":"230113","pid":{"type":"depid","value":"230113","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Transformerを用いたCOVID-19の感染者数の推移予測におけるノイズ付加の効果分析","author_link":["619080","619079"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Transformerを用いたCOVID-19の感染者数の推移予測におけるノイズ付加の効果分析"}]},"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":"法大"},{"subitem_text_value":"法大"}]},"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/230113/files/IPSJ-Z85-6U-01.pdf","label":"IPSJ-Z85-6U-01.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-6U-01.pdf","filesize":[{"value":"571.3 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"1827afdf-5b77-40e4-8782-f960091d7652","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":"山下, 穂乃花"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"藤田, 悟"}],"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":"近年のCOVID-19の流行により、現在もCOVID-19の感染拡大が止まらない。感染者予測により医療対策などをしやすくするため、COVID-19の感染者数にノイズ付加したものをTransformerで学習し、感染者数を予測することを目的とする。COVID-19の感染は約3年前から始まっており、データ数が限られているため大規模データからの予測が難しい。そこで、ノイズを付加してデータ増強を行う。そして、ノイズ付加をするときとしないときの翌日の感染者数の推移予測を行うことで、ノイズ付加による予測性能への影響を分析する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"646","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"645","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":230113,"links":{}}