独立成分分析を用いた幹線鉄道の旅客需要波動の予測手法

カテゴリ: 論文誌(論文単位)

グループ名: 【D】産業応用部門

発行日: 2018/07/01

タイトル(英語): Forecasting Method for Long-Distance Rail Passengers' Demand Fluctuations with Independent Component Analysis

著者名: 松本　涼佑（公益財団法人鉄道総合技術研究所），奥田　大樹（公益財団法人鉄道総合技術研究所），深澤　紀子（公益財団法人鉄道総合技術研究所）

著者名(英語): Ryosuke Matsumoto (Railway Technical Research Institute), Daiki Okuda (Railway Technical Research Institute), Noriko Fukasawa (Railway Technical Research Institute)

キーワード: 独立成分分析，時系列分析，需要波動　　independent component analysis，time series analysis，demand fluctuations

要約(英語): Efficient planning of long-distance rail services requires appropriate forecasting of passengers' demand fluctuation based on historical ridership records. However, this forecast is difficult, because the records consist of a mixture of passengers' demand variations. An effective approach for achieving an appropriate forecast is to decompose it into several independent demand variation components and forecast each of them. This study applies the independent component analysis to decompose the fluctuations into several additive variation components. Then, a forecasting method for passengers' demand fluctuation is developed using the calendar structure and event venue capacity.

本誌: 電気学会論文誌D（産業応用部門誌） Vol.138 No.7 （2018）

本誌掲載ページ: 655-656 p

原稿種別: 研究開発レター／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejias/138/7/138_655/_article/-char/ja/