{"created":"2025-01-19T01:37:10.717308+00:00","updated":"2025-01-19T09:35:37.291829+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00235608","sets":["1164:2735:11468:11702"]},"path":["11702"],"owner":"44499","recid":"235608","title":["Jump Like a Frog: Optimization of Renewable Energy Prediction in Smart Gird Based on Ultra Long Term Network"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-07-15"},"_buckets":{"deposit":"be23fd82-4097-42db-a785-265ea1a57bd8"},"_deposit":{"id":"235608","pid":{"type":"depid","value":"235608","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Jump Like a Frog: Optimization of Renewable Energy Prediction in Smart Gird Based on Ultra Long Term Network","author_link":["643834","643833","643831","643832"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Jump Like a Frog: Optimization of Renewable Energy Prediction in Smart Gird Based on Ultra Long Term Network"},{"subitem_title":"Jump Like a Frog: Optimization of Renewable Energy Prediction in Smart Gird Based on Ultra Long Term Network","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2024-07-15","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Hokkaido University"},{"subitem_text_value":"Hokkaido University"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hokkaido University","subitem_text_language":"en"},{"subitem_text_value":"Hokkaido University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/235608/files/IPSJ-MPS24149011.pdf","label":"IPSJ-MPS24149011.pdf"},"date":[{"dateType":"Available","dateValue":"2026-07-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS24149011.pdf","filesize":[{"value":"1.3 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":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"9efdd537-ad65-4642-9733-127e36f06c32","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":"Xingbang, Du"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Enzhi, Zhang"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Xingbang, Du","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Enzhi, Zhang","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":"Renewable energy generation forecasting plays crucial roles in advanced smart grid and sustainable practices. Although many RNN related methods have been utilized to predict power generation time series data, they often struggle to capture very long-term correlations efficiently due to the vanishing gradient issue. To address this challenge, we have introduced the Ultra long term network model that incorporated LSTM , SKIP LSTM and Dense components. This model effectively captures long-term patterns while mitigating the vanishing gradient problem associated with capturing very long term patterns. Our application of this model to renewable power prediction has yielded better performance when compared through metrics like MSE and MAE than previous models such as LSTM, GRU and Simple RNN models in time series analysis within smart grids. The integration of this model holds promise for enhancing the intelligence of renewable energy grids.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Renewable energy generation forecasting plays crucial roles in advanced smart grid and sustainable practices. Although many RNN related methods have been utilized to predict power generation time series data, they often struggle to capture very long-term correlations efficiently due to the vanishing gradient issue. To address this challenge, we have introduced the Ultra long term network model that incorporated LSTM , SKIP LSTM and Dense components. This model effectively captures long-term patterns while mitigating the vanishing gradient problem associated with capturing very long term patterns. Our application of this model to renewable power prediction has yielded better performance when compared through metrics like MSE and MAE than previous models such as LSTM, GRU and Simple RNN models in time series analysis within smart grids. The integration of this model holds promise for enhancing the intelligence of renewable energy grids.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決(MPS)"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-07-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"11","bibliographicVolumeNumber":"2024-MPS-149"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":235608,"links":{}}