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Data-driven Train Dispatching Theories in a High-speed Rail System數(shù)據(jù)驅(qū)動(dòng)的高速鐵路列車運(yùn)行調(diào)整理論

Data-driven Train Dispatching Theories in a High-speed Rail System數(shù)據(jù)驅(qū)動(dòng)的高速鐵路列車運(yùn)行調(diào)整理論

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作 者: 文 超 黃 平 李忠燦
出版社: 西南交通大學(xué)出版社
叢編項(xiàng):
標(biāo) 簽: 暫缺

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ISBN: 9787564373030 出版時(shí)間: 2020-01-01 包裝: 平裝-膠訂
開本: 16開 頁數(shù): 字?jǐn)?shù):  

內(nèi)容簡(jiǎn)介

  本書分析了高速列車運(yùn)行數(shù)據(jù)的獲取、篩選方法,研究基于高速鐵路列車運(yùn)行實(shí)績(jī),綜合運(yùn)用現(xiàn)代統(tǒng)計(jì)方法及模型、機(jī)器學(xué)習(xí)和深度學(xué)習(xí)方法、強(qiáng)化學(xué)習(xí)理論,在解析晚點(diǎn)分布規(guī)律的基礎(chǔ)上重點(diǎn)研究數(shù)據(jù)驅(qū)動(dòng)的列車晚點(diǎn)傳播與恢復(fù)理論與方法,提出基于冗余時(shí)間運(yùn)用效率及晚點(diǎn)恢復(fù)*化的冗余時(shí)間優(yōu)化布局方法,建立數(shù)據(jù)驅(qū)動(dòng)的高速鐵路列車運(yùn)行調(diào)整理論。本書的主要內(nèi)容包括:高速列車晚點(diǎn)的宏觀分布規(guī)律;晚點(diǎn)橫向、縱向傳播的宏觀規(guī)律和微觀機(jī)理;數(shù)據(jù)驅(qū)動(dòng)的高速列車晚點(diǎn)恢復(fù)模型;基于晚點(diǎn)恢復(fù)的冗余時(shí)間布局方法;本書提煉了團(tuán)隊(duì)基于列車運(yùn)行實(shí)績(jī)開展數(shù)據(jù)驅(qū)動(dòng)高速鐵路列車運(yùn)行調(diào)整理論研究的*成果,介紹了數(shù)據(jù)科學(xué)在鐵路運(yùn)輸組織優(yōu)化領(lǐng)域的結(jié)合與應(yīng)用,能夠豐富我國(guó)鐵路列車調(diào)度指揮理論與技術(shù)體系,具有較高的理論價(jià)值。本書可以作為現(xiàn)場(chǎng)調(diào)度員的參考學(xué)習(xí)用書,強(qiáng)化基于歷史數(shù)據(jù)制定調(diào)度指揮策略、列車運(yùn)行調(diào)整方法的理論和實(shí)踐知識(shí),將為調(diào)度員制定列車運(yùn)行調(diào)整方案、行車組織預(yù)案及實(shí)施應(yīng)急組織等提供一定指導(dǎo)。另外,實(shí)現(xiàn)高速列車晚點(diǎn)傳播及恢復(fù)的預(yù)測(cè),將能夠?yàn)殍F路部門資源運(yùn)用、信息發(fā)布提供實(shí)時(shí)決策支持,為旅客出行提供更為精準(zhǔn)的實(shí)時(shí)服務(wù)信息。

作者簡(jiǎn)介

暫缺《Data-driven Train Dispatching Theories in a High-speed Rail System數(shù)據(jù)驅(qū)動(dòng)的高速鐵路列車運(yùn)行調(diào)整理論》作者簡(jiǎn)介

圖書目錄

目 錄// CONTENTS
Chapter 1  Train dispatching management with data-driven approaches:
A comprehensive review and appraisal 1
1.1  Introduction 1
1.2  Data-driven train dispatching 4
1.3  Data-driven models in train dispatching: Literature 10
1.4  Review results and further discussions 32
1.5  Conclusions 38
Chapter 2  Data-driven delay distributions of HSR trains 40
2.1  Statistical Investigation on Train Primary Delay based on Real Records:
Evidence from Wuhan-Guangzhou HSR 40
2.2  Statistical Delay Distribution Analysis on High- Speed Railway Trains 59
2.3  Temporal and SpatialDistributions of Primary Delays in a High-Speed
Rail System 69
Chapter 3  Data-driven delay propagation mechanism on horizontal 83
3.1  Cause-specific Investigation of Primary Delays of Wuhan-Guangzhou HSR 83
3.2  Modellingof Effects of Primary Delays Using High- speed Train
Operation Records 106
3.3  Modelling the influence of disturbances for real-time train dispatching 120
Chapter 4  Data-driven delay propagation mechanism on vertical 135
4.1  A hybrid model to improve the train running time prediction ability
during high-speed railway disruptions 135
4.2  A Spatiotemporal Deep Learning Framework for Train Delay Prediction
in High-speed Railway Systems 150
Chapter 5  Confliction management of HSR 166
5.1  Modelling high-speed trains using triangular fuzzy number workflow nets 166
5.2  Predicting high-speed train operation conflicts using workflow nets and
 triangular fuzzy numbers 177
Chapter 6  Delay recovery and Supplement time allocation 195
6.1  Forecasting Primary Delay Recovery of High-Speed Railway Using
Data-driven Methods 195
6.2  A data-driven time supplements allocation model for train operations
on high-speed railways 211
References 228

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