{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232637","sets":["1164:4061:11479:11513"]},"path":["11513"],"owner":"44499","recid":"232637","title":["マルチスケールな空間特徴とConvolutional LSTMを用いた変動に頑健なWiFiベース人流予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-22"},"_buckets":{"deposit":"5d148342-1a36-4644-9a4a-ad207297c3fa"},"_deposit":{"id":"232637","pid":{"type":"depid","value":"232637","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"マルチスケールな空間特徴とConvolutional LSTMを用いた変動に頑健なWiFiベース人流予測","author_link":["630288","630286","630287","630289"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"マルチスケールな空間特徴とConvolutional LSTMを用いた変動に頑健なWiFiベース人流予測"},{"subitem_title":"Fluctuation-Robust WiFi-based Crowd Flow Prediction Using Multiscale Spatial Features and Convolutional LSTM","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"City on the BigData","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-02-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"豊橋技術科学大学博士前期課程情報・知能工学専攻"},{"subitem_text_value":"豊橋技術科学大学情報・知能工学系"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Toyohashi University of Technology Graduate Programs of Computer Science and Engineering for Master's Degree","subitem_text_language":"en"},{"subitem_text_value":"Toyohashi University of Technology Department of Computer Science and Engineering","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 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雅貴"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大村, 廉"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Masataka, Usui","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ren, Ohmura","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11838947","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":"2188-8698","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"現在，AI，IoT 技術を活用して生活空間を支援するスマートシティに関する取り組みが活発である．この一環として WiFi パケットセンサを用いた人流予測が行われている．WiFi パケットセンサは Probe Request と呼ばれる信号を取得している．Probe Request と人数の間には相関関係が存在するため，Probe Request を予測することで人流を予測することが出来る．人流予測では，個人・対象地域ごとの個別かつ定常時の予測が多い．そのため，地域関係を考慮してイベントなどの突発的な変動に対処した人流予測が少ない課題が存在する．それに対して Convolutional LSTM （ConvLSTM）やマルチスケール特徴畳み込みブロックを用いることで，地域関係や突発的な変動を考慮した予測手法として気象予測がある．そこで本研究では，気象予測手法を取り入れ，地域関係と突発的な変動であるイベントを考慮した ConvLSTM ベースの人流予測モデルを提案し，Probe Request の予測精度を既存モデルと比較する．Kernel Size を変化させたマルチスケール特徴畳み込みブロックを従来手法である 3 層の ConvLSTMモ デルに組み込むことで，イベント時であっても決定係数が 0.86 以上と，イベント時の人流予測の精度を向上することを確認できた．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告ユビキタスコンピューティングシステム（UBI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-02-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"33","bibliographicVolumeNumber":"2024-UBI-81"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":232637,"updated":"2025-01-19T10:22:59.704747+00:00","links":{},"created":"2025-01-19T01:33:37.239234+00:00"}