{"updated":"2025-01-20T13:10:30.807060+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00157940","sets":["1164:3980:8489:8490"]},"path":["8490"],"owner":"11","recid":"157940","title":["確率的最適化による深層学習とマルチエレメントGAを用いた道路交通信号パラメータの最適化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-02-29"},"_buckets":{"deposit":"33e46b83-7b1d-4098-b1cf-b0a7c479d943"},"_deposit":{"id":"157940","pid":{"type":"depid","value":"157940","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"確率的最適化による深層学習とマルチエレメントGAを用いた道路交通信号パラメータの最適化","author_link":["300271","300273","300267","300272","300269","300266","300268","300270"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"確率的最適化による深層学習とマルチエレメントGAを用いた道路交通信号パラメータの最適化"},{"subitem_title":"Optimization of road traffic signal parameters using a multi-element GA and deep learning by stochastic optimization","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"交通流","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2016-02-29","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"崇城大学"},{"subitem_text_value":"崇城大学"},{"subitem_text_value":"熊本大学"},{"subitem_text_value":"熊本大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Sojo University","subitem_text_language":"en"},{"subitem_text_value":"Sojo University","subitem_text_language":"en"},{"subitem_text_value":"Kumamoto University","subitem_text_language":"en"},{"subitem_text_value":"Kumamoto 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/157940/files/IPSJ-ITS16064004.pdf","label":"IPSJ-ITS16064004.pdf"},"date":[{"dateType":"Available","dateValue":"2018-02-28"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ITS16064004.pdf","filesize":[{"value":"491.0 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":"37"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"9a741a37-dd2e-42c5-bfcf-f9b80039f492","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"中村, 新之介"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"植村, 匠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"上瀧, 剛"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"内村, 圭一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shinnnosuke, Nakamura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takumi, Uemura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Gou, Koutaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Keiichi, Uchimura","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11515904","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":"2188-8965","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，交通渋滞を緩和する手法として交通信号機制御による手法が注目されている．筆者らはマルチエレメント GA と交通流シミュレータを用いて交通信号パラメータを最適化し，渋滞を緩和する手法が提案したが，最適化処理に長い時間を要するため，実環境下での運用は現実的ではない問題を有していた．本研究では，交通流シミュレータの入出力関係を学習させた学習機械をシミュレータと置き換える手法を提案し，最適化処理の時間短縮を目指す．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In recent years, techniques have been attracting attention due to traffic signal control as a method to alleviate traffic congestion. Among them, Mitigation method congestion by optimizing the traffic signal parameters using multi-element GA and traffic simulator was proposed. But it takes a long time to the optimization process. Therefore, It is difficult to operating in a real environment. In this study, in order to shorten the optimization process time, we propose a method to replace the learning machine to the traffic flow simulator.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告高度交通システムとスマートコミュニティ（ITS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2016-02-29","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"2016-ITS-64"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2025-01-19T00:31:44.343836+00:00","id":157940,"links":{}}