{"id":214705,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00214705","sets":["6504:10735:10805"]},"path":["10805"],"owner":"44499","recid":"214705","title":["変分推論・非線形フィルタリングを駆使した時系列データの潜在モデルの推論・予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"12d779f5-e2d7-4c2f-83f3-47e2a058a683"},"_deposit":{"id":"214705","pid":{"type":"depid","value":"214705","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"変分推論・非線形フィルタリングを駆使した時系列データの潜在モデルの推論・予測","author_link":["551962","551963","551964"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"変分推論・非線形フィルタリングを駆使した時系列データの潜在モデルの推論・予測"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ソフトウェア科学・工学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2021-03-04","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":"明大"},{"subitem_text_value":"中大"},{"subitem_text_value":"明治大/JSTさきがけ"}]},"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/214705/files/IPSJ-Z83-4J-03.pdf","label":"IPSJ-Z83-4J-03.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-28"}],"format":"application/pdf","filename":"IPSJ-Z83-4J-03.pdf","filesize":[{"value":"424.8 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"8b04db2c-78ed-4bec-8875-e17a95e74f07","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"石曽根, 毅"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"樋口, 知之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, 和幸"}],"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":"時系列データが従うモデルを同定することは，予測・制御等において極めて重要な意義を持つ．この目的を達成するために，確率的 RNN モデルと粒子フィルタを活用した手法である FIVOs が注目を集めている．しかし，FIVOs は粒子の退化による学習効率の低下・学習コストの増大といった問題を抱えている．本発表では，これらを解決する新しい潜在モデルの推論手法として，確率的 RNN モデルと EnKF を組み合わせた手法を提案する．提案手法は，シミュレーションデータ・実データに対し，既存研究を上回る予測精度を達成し，解釈可能性のある結果が提供できたことを報告する．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"192","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"191","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T16:30:26.622256+00:00","created":"2025-01-19T01:15:30.456595+00:00","links":{}}