{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00194470","sets":["1164:2735:9724:9725"]},"path":["9725"],"owner":"44499","recid":"194470","title":["Fast Railway Delay Evaluation Method Based on Discrete Distribution Propagation"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-02-21"},"_buckets":{"deposit":"e341efe7-a113-4f49-8609-e07ae64d92fa"},"_deposit":{"id":"194470","pid":{"type":"depid","value":"194470","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Fast Railway Delay Evaluation Method Based on Discrete Distribution Propagation","author_link":["460370","460374","460372","460371","460369","460373"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Fast Railway Delay Evaluation Method Based on Discrete Distribution Propagation"},{"subitem_title":"Fast Railway Delay Evaluation Method Based on Discrete Distribution Propagation","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2019-02-21","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Toshiba Corporation"},{"subitem_text_value":"Toshiba Corporation"},{"subitem_text_value":"Toshiba Digital Solutions Corporation"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Toshiba Corporation","subitem_text_language":"en"},{"subitem_text_value":"Toshiba Corporation","subitem_text_language":"en"},{"subitem_text_value":"Toshiba Digital Solutions Corporation","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/194470/files/IPSJ-MPS19122007.pdf","label":"IPSJ-MPS19122007.pdf"},"date":[{"dateType":"Available","dateValue":"2021-02-21"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS19122007.pdf","filesize":[{"value":"887.2 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":"b2bbf50e-ba8c-485f-8725-ee082b2e4fe7","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tomoshi, Otsuki"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideo, Sakamoto"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideki, Kubo"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tomoshi, Otsuki","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideo, Sakamoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideki, Kubo","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":"Accurate delay evaluation of timetables is crucial for railway companies. There have been some conventional methods utilizing continuous random variables directly. These methods, however, suffer combinatorial expansion problems, which require complex pruning techniques. In this paper, discretizing the delay distribution on railway networks, we present a method calculating propagated delay distributions on each event analytically under the assumption of propagated delays' independence. We also show the complexity of the proposed method is O (M²N) in the general case and can be reduced to O (MN) especially for the special cases where the source distribution is the negative binominal distribution, where M denotes the number of quantization levels in discretization and N denotes the total number of events. Finally, computational experiments on test scenarios with M ～ 700 show that the proposed method provides almost same results as and in over 500 times faster computation time than Monte Carlo simulations.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Accurate delay evaluation of timetables is crucial for railway companies. There have been some conventional methods utilizing continuous random variables directly. These methods, however, suffer combinatorial expansion problems, which require complex pruning techniques. In this paper, discretizing the delay distribution on railway networks, we present a method calculating propagated delay distributions on each event analytically under the assumption of propagated delays' independence. We also show the complexity of the proposed method is O (M²N) in the general case and can be reduced to O (MN) especially for the special cases where the source distribution is the negative binominal distribution, where M denotes the number of quantization levels in discretization and N denotes the total number of events. Finally, computational experiments on test scenarios with M ～ 700 show that the proposed method provides almost same results as and in over 500 times faster computation time than Monte Carlo simulations.","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":"2019-02-21","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"7","bibliographicVolumeNumber":"2019-MPS-122"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":194470,"updated":"2025-01-19T23:28:25.578182+00:00","links":{},"created":"2025-01-19T00:59:31.310136+00:00"}