交通大數(shù)據(jù)分析(英文版)/一帶一路鐵路國(guó)際人才教育叢書(shū)
定 價(jià):68 元
叢書(shū)名:一帶一路鐵路國(guó)際人才教育叢書(shū)
- 作者:田紅旗,陳春陽(yáng)著,王璞,郭寶編
- 出版時(shí)間:2023/3/1
- ISBN:9787548752936
- 出 版 社:中南大學(xué)出版社
- 中圖法分類(lèi):U495
- 頁(yè)碼:104
- 紙張:
- 版次:1
- 開(kāi)本:16開(kāi)
In this book, Chapter 1 will introduce various types of transportation big data, and the challenges in the transportation big data analysis; Chapter 2 will introduce the data structures and the data properties of common transportation big data; Chapter 3 will introduce the preprocessing methods of transportation big data; Chapter 4 will introduce some useful tools for analyzing transportation networks and human mobility; In Chapter 5, the advantages of data fusion approaches will be discussed, and four transportation data fusion cases will be introduced; and finally Chapter 6 will introduce five transportation big data applications to strengthen readers' understanding of the methods presented in Chapters 2, 3, 4.
Chapter 1 Introduction
1.1 Big data technology
1.2 A brief introduction of transportation big data
1.3 Challenges in the transportation big data analysis
1.4 The applications of transportation big data
1.5 Brief introduction of the following chapters
Chapter 2 Data structures and properties of transportation big data
2.1 Geographic information data
2.2 Vehicle GPS data
2.3 Smart card data
2.4 Vehicle identification data
2.5 Mobile phone data
Chapter 3 Transportation big data preprocessing
3.1 Basic steps of data preprocessing
3.2 Data preprocessing of geographic information data
3.3 Data preprocessing of vehicle GPS data
3.4 Data preprocessing of smart card data
3.5 Data preprocessing of license plate recognition data
3.6 Data preprocessing of mobile phone data for transportation
4.1 A method for generating transportation networks
4.2 Fundamental network analysis tools
4.3 Network modeling and analysis for individual mobility
4.4 Network modeling and analysis of collective mobility
4.5 Network percolation analysis
Chapter 5 Multi-source trans~rtation big data fusion and analysis
5.1 Characteristics of different transportation big data
5.2 Insights for developing transportation big data fusion approaches
5.3 Data fusion of multi-source vehicle GPS data
5.4 Data fusion of LPR data and taxi GPS data
5.5 Data fusion of MS data, subway smart card data and taxi GPS data
Chapter 6 Applications tran~ortation big data
6.1 Application of CDR data in estimating travel demand
6.2 Application of CDR data in identifying vehicle sources
6.3 Applications of transportation big data in deploying congestion mitigation strategies
6.4 Application of transportation big data in anticipating large crowd gatherings
6.5 Application of open-source data in predicting subway passenger flow
References