{"id":218609,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00218609","sets":["1164:2735:10865:10962"]},"path":["10962"],"owner":"44499","recid":"218609","title":["並列リンケージ同定を用いた進化計算による合成人口モデルの生成"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-06-20"},"_buckets":{"deposit":"77701ef8-a214-4c12-b3ed-d8506634e368"},"_deposit":{"id":"218609","pid":{"type":"depid","value":"218609","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"並列リンケージ同定を用いた進化計算による合成人口モデルの生成","author_link":["568939","568942","568941","568940"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"並列リンケージ同定を用いた進化計算による合成人口モデルの生成"},{"subitem_title":"Generation of Synthetic Population Models by Evolutionary Computation Using Parallel Linkage Identification","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2022-06-20","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"北海道大学大学院情報科学院"},{"subitem_text_value":"北海道大学大学院情報科学院／北海道大学情報基盤センター"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate Schools of Information Science and Technology, Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Graduate Schools of Information Science and Technology, Hokkaido University / Information Initiative Center, Hokkaido 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/218609/files/IPSJ-MPS22138039.pdf","label":"IPSJ-MPS22138039.pdf"},"date":[{"dateType":"Available","dateValue":"2024-06-20"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS22138039.pdf","filesize":[{"value":"498.9 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"429150b6-96e1-4b4e-bcb3-5520b92713c5","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"細川, 喜生"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"棟朝, 雅晴"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yoshiki, Hosokawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masaharu, Munetomo","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","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":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，社会シミュレーションの発展により，それに用いる市民の年齢，性別，収入，職業，学歴などの属性を統計データから復元することが求められている．しかし，これらの属性はプライバシー等の理由から保護されており，シミュレーションにて利用するためには信頼性の高い復元手法が求められる．疑似焼きなまし法や進化計算による最適化手法が提案されているが，年齢に対して最適化を行うために世帯数や総人口について事前の調整が必要であり，計算高速化のために用いられている並列計算では，統計データの分割による誤差の増加という問題点がある．そこで本論文では，リンケージ同定を用いることで，細かな初期世帯の設定を行わずに世帯間の相互関係を用いて複数の市民属性を統計データからの最適化し，より現実に近い人口データの作成を試みる．また，並列計算によりリンケージ同定を行うことで，データを分割せずに計算の高速化を試みる手法を提案する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"2","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-06-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"39","bibliographicVolumeNumber":"2022-MPS-138"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T15:06:32.604449+00:00","created":"2025-01-19T01:18:57.878493+00:00","links":{}}