{"created":"2025-01-19T00:47:43.361860+00:00","updated":"2025-01-20T05:09:32.541067+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00178370","sets":["1164:8666:9126:9127"]},"path":["9127"],"owner":"11","recid":"178370","title":["機械学習による高齢者支援者向け移動時間の想定法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-03-03"},"_buckets":{"deposit":"aa0efb85-0d41-4bf6-ab47-18b245f80b19"},"_deposit":{"id":"178370","pid":{"type":"depid","value":"178370","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"機械学習による高齢者支援者向け移動時間の想定法","author_link":["381769","381765","381772","381770","381766","381767","381771","381773","381774","381768"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習による高齢者支援者向け移動時間の想定法"},{"subitem_title":"Assumption Method of Travel Time for Elderly Supporters by Machine Learning","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"高齢者（2） ","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2017-03-03","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"茨城県立産業技術短期大学校"},{"subitem_text_value":"茨城県立産業技術短期大学校"},{"subitem_text_value":"茨城県立産業技術短期大学校"},{"subitem_text_value":"茨城県立産業技術短期大学校"},{"subitem_text_value":"茨城県立産業技術短期大学校"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Ibaraki Prefectural Junior College of Industrial Technology","subitem_text_language":"en"},{"subitem_text_value":"Ibaraki Prefectural Junior College of Industrial Technology","subitem_text_language":"en"},{"subitem_text_value":"Ibaraki Prefectural Junior College of Industrial Technology","subitem_text_language":"en"},{"subitem_text_value":"Ibaraki Prefectural Junior College of Industrial Technology","subitem_text_language":"en"},{"subitem_text_value":"Ibaraki Prefectural Junior College of Industrial Technology","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/178370/files/IPSJ-AAC17003026.pdf","label":"IPSJ-AAC17003026.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-AAC17003026.pdf","filesize":[{"value":"277.1 kB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"52"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"456bcf1d-d0fa-4976-a15f-2718bbab4912","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2017 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":"石井, 智恵美"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐々木, 祐輔"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"赤津, 遥香"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"小林, 守"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石川, 広幸"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Chiemi, Ishii","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yusuke, Sasaki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Haruka, Akatsu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Mamoru, Kobayashi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroyuki, Ishikawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12752949","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":"2432-2431","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年， 自宅で介護を受ける高齢者が増えている．高齢者宅に介護支援者が移動する時間を求めるのに複数の手法がある．従来の研究では Google Map ツールから移動時間を求める方法と，複数データから得た平均値と偏差値を考盧して求める方法を提案したが，平均値と偏差値では実際の時間とは大きく異なる問題があった．本研究では，より実測時間に近づけるために機械学習を用いた移動時間を想定する方法を提案する．具体的には，Google Maps ツールを用いて移動時間を求め，次に複数の実測データから機械学習して移動時間を得る手法を開発した．本報告では，Google Maps ツールや複数データから機械学習し移動時間を求める手法について紹介する．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Recently, there is increasing the number of elderly living with assistance of elderly supporters at the home. There is problem with a method for assuming travel time for efficient movement between elderly residents in elderly supporters. In previous research, we proposed with a method considering the average time and deviation time obtained from actual moving time and the mobbing time of Google Maps Tool. As a result, the travel time considering the average time the deviation time has been different from the actual travel time. In this research, we propose a method to estimate travel time using Google's travel time data and machine teaming data. Specifically, we developed a method to assume new travel time using travel time taken out of Google cloud using Google Map tool and the ratio get in machine learning from actual travel time of elderly supporters. In this report, we will show you how to estimate travel time using Google Map tool and machine learning. ","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告アクセシビリティ（AAC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2017-03-03","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"26","bibliographicVolumeNumber":"2017-AAC-3"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":178370,"links":{}}