{"updated":"2025-01-19T11:22:37.260448+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229886","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229886","title":["栽培データの不均衡性・時系列を考慮した植物生理状態の推定手法の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"70c007bf-318f-4582-b1d7-d438cf1cf49f"},"_deposit":{"id":"229886","pid":{"type":"depid","value":"229886","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"栽培データの不均衡性・時系列を考慮した植物生理状態の推定手法の検討","author_link":["618405","618404","618403","618401","618402"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"栽培データの不均衡性・時系列を考慮した植物生理状態の推定手法の検討"}]},"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":"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":"静岡大"},{"subitem_text_value":"静岡大"},{"subitem_text_value":"静岡県農林技研"},{"subitem_text_value":"静岡県農林技研"},{"subitem_text_value":"静岡大"}]},"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/229886/files/IPSJ-Z85-7P-05.pdf","label":"IPSJ-Z85-7P-05.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-7P-05.pdf","filesize":[{"value":"786.1 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"b64500c2-d7ce-4165-bdf0-6ff4e61c7ff2","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":"佐藤, 弘毅"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"藤浪, 一輝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大石, 直記"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"二俣, 翔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"峰野, 博史"}],"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":"就農者の不足や，熟練農家の技術の消失といった課題に対してスマート農業の実現に向けた取り組みが行なわれている．本研究では低コストかつ非接触なセンサデータから機械学習で植物生理状態を推定する手法を検討する．機械学習を用いる場合に，栽培データの不均衡性や時系列性に課題がある．不均衡性を解消するリサンプリング手法であるREAMER(Clustering-based REsAmpling MEthod for Regression)を改良し，時系列性を考慮した学習手法を用いて，イチゴの光合成速度と蒸発散速度について推定し，既存のリサンプリング手法とCREAMERを適用した際の推定精度の比較検証を行った．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"174","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"173","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:29:19.050731+00:00","id":229886,"links":{}}