{"updated":"2025-01-19T09:56:30.247979+00:00","links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00233907","sets":["1164:2836:11471:11602"]},"path":["11602"],"owner":"44499","recid":"233907","title":["レーダ雨量および流水距離を用いた転移学習による増水時の河川水位予測の試み"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-05-08"},"_buckets":{"deposit":"16beefe9-c4e0-4387-a8bf-7c3d6922ebf2"},"_deposit":{"id":"233907","pid":{"type":"depid","value":"233907","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"レーダ雨量および流水距離を用いた転移学習による増水時の河川水位予測の試み","author_link":["636406","636404","636405","636407"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"レーダ雨量および流水距離を用いた転移学習による増水時の河川水位予測の試み"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[MBL]センシングとIoT","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-05-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"和歌山大学大学院システム工学研究科"},{"subitem_text_value":"和歌山大学システム工学部"},{"subitem_text_value":"和歌山大学システム工学部"},{"subitem_text_value":"和歌山大学システム工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Wakayama University","subitem_text_language":"en"},{"subitem_text_value":"Wakayama University","subitem_text_language":"en"},{"subitem_text_value":"Wakayama University","subitem_text_language":"en"},{"subitem_text_value":"Wakayama University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/233907/files/IPSJ-DPS24199040.pdf","label":"IPSJ-DPS24199040.pdf"},"date":[{"dateType":"Available","dateValue":"2026-05-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DPS24199040.pdf","filesize":[{"value":"11.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"34"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"b8a9413b-6020-45e3-8645-9e911cab8422","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"上田, 風斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田内, 裕人"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"江種, 伸之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"吉廣, 卓哉"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10116224","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8906","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"洪水時の正確な河川水位予測は，住民の適切な避難判断に役立てるために重要であり，盛んに研究が行われている．従来の深層学習を用いた河川水位予測手法では，上流の水位と雨量観測所から下流の水位観測所の水位を予測している．しかし，日本の多くの中小河川では，複数の観測所がある場合は少なく，正確な水位予測を行うことが難しい．そこで本研究では，上流観測所の水位と雨量を用いずに，予測地点の水位観測値と気象庁が観測するレーダ雨量を用いて水位予測を行う．河川水位予測モデルとしては，深層学習モデルである CNN と LSTM を組み合わせた予測モデルを構築し，新たに定義する流水距離データを用いた転移学習手法を提案する．評価の結果，水位観測所が一つしかなく，過去の増水時のデータ数が少ない場合でも，提案手法により，一定精度の水位予測が可能であることを示した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告マルチメディア通信と分散処理（DPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-05-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"40","bibliographicVolumeNumber":"2024-DPS-199"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":233907,"created":"2025-01-19T01:35:33.382665+00:00"}