{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00213763","sets":["1164:2592:10486:10744"]},"path":["10744"],"owner":"44499","recid":"213763","title":["AI 技術を用いたビル設備の制御手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-11-11"},"_buckets":{"deposit":"b659fdf0-0a92-437e-b927-9886363ea248"},"_deposit":{"id":"213763","pid":{"type":"depid","value":"213763","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"AI 技術を用いたビル設備の制御手法の提案","author_link":["547297","547301","547300","547299","547306","547303","547302","547305","547304","547298"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"AI 技術を用いたビル設備の制御手法の提案"},{"subitem_title":"A Proposal of the Control Method for Multiple Buildings with AI Techniques","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2021-11-11","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学情報理工学系研究科電子情報学専攻"},{"subitem_text_value":"東京大学情報理工学系研究科電子情報学専攻"},{"subitem_text_value":"東京大学情報理工学系研究科電子情報学専攻"},{"subitem_text_value":"東京大学情報理工学系研究科電子情報学専攻"},{"subitem_text_value":"東京大学情報理工学系研究科電子情報学専攻"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Information Science and Technology, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science and Technology, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science and Technology, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science and Technology, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Information Science and Technology, The University of Tokyo","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/213763/files/IPSJ-AL21185002.pdf","label":"IPSJ-AL21185002.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-AL21185002.pdf","filesize":[{"value":"2.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"9"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"1125b933-ed69-487f-bcd9-ff2a6e3cc207","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"藤田, 航輝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"藤村, 柊吾"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"孫, 昱偉"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"江崎, 浩"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"落合, 秀也"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Koki, Fujita","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shugo, Fujimura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yu, Wei Sun","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroshi, Esaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideya, Ochiai","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN1009593X","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":"2188-8566","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年ビル設備の制御に AI 技術を用いる手法が提案され始めている．将来のビル設備にはエアコン設備だけでなく太陽光パネル，蓄電池など様々な電力設備が取り付けられると考えられるため機械学習を用いて，それらを効率的に制御できることが期待される．しかし現在までの研究において，複数の対象を同時に制御する方法や，また複数のビルの電気設備を同時に制御するという複雑な状況設定における研究は少ない．そこで本研究では複数のビルがあり，各ビルにはエアコン設備や太陽光パネル，蓄電池が取り付けられているという状況を設定する．また機械学習手法として，各ビルは強化学習を用いて学習を行ない，複数のビルのモデルの情報を集約し全体としての学習を行う方法として連合学習を用いるという手法の提案を行なう．提案手法の性能を検証するため，シミュレータ上で各ビルのエアコンの設定温度の制御という実験を行ない，複数のビルでの連合学習を行うことでその性能の向上を確認した．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In recent years, the use of AI techniques for controlling building facilities has begun to be proposed. In the future, buildings will be equipped with not only air conditioners but also solar panels, storage batteries, and a variety of other power equipment, and it is expected that machine learning can be used to control them efficiently. However, there have been few studies on how to control multiple targets simultaneously, or on complex situations in which electrical equipment in multiple buildings is controlled simultaneously. In this study, we set up a situation where there are multiple buildings and each building has air-conditioning equipment, solar panels, and storage batteries. As a machine learning method, we propose a method that uses reinforcement learning for each building and federated learning for the whole system by aggregating the information from multiple building models. In order to verify the performance of the proposed method, we conducted experiments to control the set temperature of air conditioners in each building on a simulator, and confirmed that the performance of the proposed method was improved by using federated learning in multiple buildings.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告アルゴリズム（AL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-11-11","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2021-AL-185"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":213763,"updated":"2025-01-19T17:01:56.721617+00:00","links":{},"created":"2025-01-19T01:14:36.701878+00:00"}