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220319s2022 si | s |||| 0|eng d |
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|a 9789811680083
|9 978-981-16-8008-3
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|a 10.1007/978-981-16-8008-3
|2 doi
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|a 300.00285
|2 23
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|a Yang, Fei.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Travel Behavior Characteristics Analysis Technology Based on Mobile Phone Location Data
|h [electronic resource] :
|b Methodology and Empirical Research /
|c by Fei Yang, Zhenxing Yao.
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| 250 |
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|a 1st ed. 2022.
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| 264 |
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|a Singapore :
|b Springer Nature Singapore :
|b Imprint: Springer,
|c 2022.
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| 300 |
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|a XXII, 217 p. 122 illus., 107 illus. in color.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Chapter 1. Introduction -- Chapter 2. 2 Literature Review -- Chapter 3. Methodology for Mobile Phone Location Data Mining -- Chapter 4. Mobile Phone Sensor Data Collection And Analysis -- Chapter 5. Pedestrian-Traffic Flow-Communication’ Integrated Simulation Platform Construction -- Chapter 6. Empirical Study on Trip Information Extraction Based on Mobile Phone Sensor Data -- Chapter 7. Influence Parameters and Sensitivity Analysis -- Chapter 8. Thinking about Application of Refined Travel Data in Traffic Planning -- Chapter 9. Outlook -- Appendix.
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|a This book is devoted to the technology and methodology of individual travel behavior analysis and refined travel information extraction. Traditional resident trip surveys are characterized by many shortcomings, such as subjective memory errors, difficulty in organization and high cost. Therefore, in this book, a set of refined extraction and analysis techniques for individual travel activities is proposed. It provides a solid foundation for the optimization and reconstruction of traffic theoretical models, urban traffic planning, management and decision-making. This book helps traffic engineering researchers, traffic engineering technicians and traffic industry managers understand the difficulties and challenges faced by transportation big data. Additionally, it helps them adapt to changes in traffic demand and the technological environment to achieve theoretical innovation and technological reform.
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| 650 |
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|a Social sciences
|x Data processing.
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| 650 |
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|a Quantitative research.
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| 650 |
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|a Sociology
|x Methodology.
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| 650 |
1 |
4 |
|a Computer Application in Social and Behavioral Sciences.
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| 650 |
2 |
4 |
|a Data Analysis and Big Data.
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| 650 |
2 |
4 |
|a Sociological Methods.
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| 700 |
1 |
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|a Yao, Zhenxing.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer Nature eBook
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| 776 |
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|i Printed edition:
|z 9789811680076
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| 776 |
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|i Printed edition:
|z 9789811680090
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| 776 |
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|i Printed edition:
|z 9789811680106
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| 856 |
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|u https://doi.org/10.1007/978-981-16-8008-3
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| 912 |
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|a ZDB-2-BSP
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| 912 |
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|a ZDB-2-SXBP
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| 950 |
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|a Behavioral Science and Psychology (SpringerNature-41168)
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| 950 |
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|a Behavioral Science and Psychology (R0) (SpringerNature-43718)
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