滿額折
數據驅動的高速鐵路列車運行調整理論 Data-driven Train Dispatching Theories in a High-speed Rail System（簡體書）
商品資訊
系列名：高等學校交通運輸專業教材
ISBN13：9787564373030
替代書名：Data-driven Train Dispatching Theories in a High-speed Rail System
出版社：西南交通大學出版社
作者：文超
出版日：2020/01/10
裝訂：平裝
規格：24cm*17cm (高/寬)
商品簡介
目次
商品簡介
本書分析了高速列車運行數據的獲取、篩選方法，研究基於高速鐵路列車運行實績，綜合運用現代統計方法及模型、機器學習和深度學習方法、強化學習理論，在解析晚點分佈規律的基礎上重點研究數據驅動的列車晚點傳播與恢復理論與方法，提出基於冗餘時間運用效率及晚點恢復最大化的冗餘時間優化佈局方法，建立數據驅動的高速鐵路列車運行調整理論。本書的主要內容包括：高速列車晚點的宏觀分佈規律；晚點橫向、縱向傳播的宏觀規律和微觀機理；數據驅動的高速列車晚點恢復模型；基於晚點恢復的冗餘時間佈局方法；本書提煉了團隊基於列車運行實績開展數據驅動高速鐵路列車運行調整理論研究的最新成果，介紹了數據科學在鐵路運輸組織優化領域的結合與應用，能夠豐富我國鐵路列車調度指揮理論與技術體系，具有較高的理論價值。本書可以作為現場調度員的參考學習用書，強化基於歷史數據制定調度指揮策略、列車運行調整方法的理論和實踐知識，將為調度員制定列車運行調整方案、行車組織預案及實施應急組織等提供一定指導。另外，實現高速列車晚點傳播及恢復的預測，將能夠為鐵路部門資源運用、信息發佈提供實時決策支持，為旅客出行提供更為精准的實時服務信息。
目次
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
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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