{"id":209718,"created":"2025-01-19T01:11:00.540299+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00209718","sets":["1164:2735:10526:10527"]},"path":["10527"],"owner":"44499","recid":"209718","title":["電力需要予測に対するモデルベース時系列クラスタリングの応用"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-02-22"},"_buckets":{"deposit":"374a119d-6eb7-453f-8626-083d5960e53c"},"_deposit":{"id":"209718","pid":{"type":"depid","value":"209718","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"電力需要予測に対するモデルベース時系列クラスタリングの応用","author_link":["529421","529424","529423","529418","529420","529422","529425","529419"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"電力需要予測に対するモデルベース時系列クラスタリングの応用"},{"subitem_title":"Application of Model-Based Time Series Clustering to Electricity Demand Forecasting","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2021-02-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"滋賀大学"},{"subitem_text_value":"滋賀大学"},{"subitem_text_value":"滋賀大学"},{"subitem_text_value":"大阪ガス（株）情報通信部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Shiga University","subitem_text_language":"en"},{"subitem_text_value":"Shiga University","subitem_text_language":"en"},{"subitem_text_value":"Shiga University","subitem_text_language":"en"},{"subitem_text_value":"Information/Communication Systems Dept., Osaka Gas Co., Ltd.","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/209718/files/IPSJ-MPS21132018.pdf","label":"IPSJ-MPS21132018.pdf"},"date":[{"dateType":"Available","dateValue":"2023-02-22"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS21132018.pdf","filesize":[{"value":"857.2 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":"f1e70010-1e86-4b24-8643-c223799a92c0","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"白瀧, 豪"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"今井, 貴史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"河本, 薫"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"國政, 秀太郎"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Go, Shirataki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takashi, Imai","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kaoru, Kawamoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shutaro, Kunimasa","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":"電力事業において，電力は貯めておくことが難しいエネルギーであるため，電力需要を予測して需要と供給のバランスを整えることが必要になる．しかし，事業開始直後などは顧客数が少ないため，全顧客の需要合計を一括して予測しても，充分な精度がえられなかった．そこで，本研究では予測精度を上げることを目的とし，その達成のためにクラスタリングとクラスターごとのモデル推定を同時に行うことができる混合 ARMA モデルを用いた時系列クラスタリングを適用した．その結果，全顧客を一つの ARMA モデルで説明する場合や顧客ごとに ARMA モデルで説明する場合のどちらよりも予測精度を向上させられることが確認できた．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In the electric power business, since electricity is an energy source that is difficult to store, it is necessary to forecast electricity demand to maintain a balance between supply and demand. However, due to the small number of customers immediately after the start of the business, it is often not possible to obtain sufficient accuracy by directly forecasting the total demand of all customers. In this study, in order to improve the forecasting accuracy, we applied a model-based method for time series clustering, which can simultaneously perform clustering and model estimation for each cluster. The results confirm that this method provides better prediction accuracy than both the case where one model is defined for all customers and the case where a model is defined for each customer.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-02-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"18","bibliographicVolumeNumber":"2021-MPS-132"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T18:25:35.020086+00:00","links":{}}