{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00236736","sets":["6504:11678:11684"]},"path":["11684"],"owner":"44499","recid":"236736","title":["深層学習による数値気象モデル予測結果補正手法の改良とその豪雨緩和効果予測への活用へ向けた検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"75617e41-fad6-4a4e-b7d9-a5584cad4654"},"_deposit":{"id":"236736","pid":{"type":"depid","value":"236736","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"深層学習による数値気象モデル予測結果補正手法の改良とその豪雨緩和効果予測への活用へ向けた検討","author_link":["647276","647275","647273","647274","647272"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"深層学習による数値気象モデル予測結果補正手法の改良とその豪雨緩和効果予測への活用へ向けた検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"コンピュータと人間社会","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2024-03-01","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":"山梨大"},{"subitem_text_value":"山梨大"},{"subitem_text_value":"日本工営株式会社"},{"subitem_text_value":"法大"},{"subitem_text_value":"九大"}]},"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/236736/files/IPSJ-Z86-5F-04.pdf","label":"IPSJ-Z86-5F-04.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-04"}],"format":"application/pdf","filename":"IPSJ-Z86-5F-04.pdf","filesize":[{"value":"361.2 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"c8a55173-2758-4e13-b014-498fe26b93ff","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"相馬, 一義"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"松田, 聖矢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"倉上, 健"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鈴木, 善晴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西山, 浩司"}],"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，人為的操作によりハザードとなる豪雨を緩和する検討が開始されており，数値気象モデルにより高い信頼性で効果を予測することが求められている．本研究では，豪雨緩和効果予測への活用を目指し，深層学習による数値気象モデル予測結果正手法を，データ拡張に注目して改良した．その結果，データ拡張におけるストライドを大きくすることにより，台風に伴う豪雨について降水量予測精度が改善するが示唆された．今後は前線に伴う豪雨等でも効果が得られるよう改良が望まれる．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"246","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"245","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":236736,"updated":"2025-01-19T09:08:35.751397+00:00","links":{},"created":"2025-01-19T01:38:57.547181+00:00"}