{"id":214815,"updated":"2025-01-19T16:27:18.959261+00:00","links":{},"created":"2025-01-19T01:15:36.679212+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00214815","sets":["6504:10735:10808"]},"path":["10808"],"owner":"44499","recid":"214815","title":["浄水処理における深層学習を用いた凝集後濁度予測の精度向上手法の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-03-04"},"_buckets":{"deposit":"bc380ae4-d813-4302-8d9d-bef075194c37"},"_deposit":{"id":"214815","pid":{"type":"depid","value":"214815","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"浄水処理における深層学習を用いた凝集後濁度予測の精度向上手法の検討","author_link":["552790","552791","552793","552792","552794"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"浄水処理における深層学習を用いた凝集後濁度予測の精度向上手法の検討"}]},"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":"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":"北海道科学大"},{"subitem_text_value":"北海道科学大"},{"subitem_text_value":"中大"},{"subitem_text_value":"前澤工業"},{"subitem_text_value":"北海道科学大"}]},"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/214815/files/IPSJ-Z83-2C-05.pdf","label":"IPSJ-Z83-2C-05.pdf"},"date":[{"dateType":"Available","dateValue":"2021-12-28"}],"format":"application/pdf","filename":"IPSJ-Z83-2C-05.pdf","filesize":[{"value":"870.9 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"aa7062cf-b36e-4683-92d0-9cd71278768d","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":"鈴木, 昭弘"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"川上, 敬"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山, 寛"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"根本, 雄一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大江, 亮介"}],"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":"浄水場における浄水処理において、適切な量の凝集剤を注入することにより良質なフロック（懸濁質の塊り）を形成することは非常に重要である。本研究の最終的な目的は凝集剤の注入を適切に自動制御することである。そこでその第一段階として深層学習を用いて凝集剤を注入し形成中の初期のフロックの画像的な特徴から凝集後の濁度を予測する研究を行っている。本発表では予測精度を向上させるために、いくつかのデータ水増し手法が凝集後濁度予測に適しているかどうかについて検討しその結果を述べる。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"18","bibliographic_titles":[{"bibliographic_title":"第83回全国大会講演論文集"}],"bibliographicPageStart":"17","bibliographicIssueDates":{"bibliographicIssueDate":"2021-03-04","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}