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Logic-driven traffic big data analyt...
~
Zhong, Shaopeng.
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Logic-driven traffic big data analytics = methodology and applications for planning /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Logic-driven traffic big data analytics/ by Shaopeng Zhong, Daniel (Jian) Sun.
Reminder of title:
methodology and applications for planning /
Author:
Zhong, Shaopeng.
other author:
Sun, Daniel.
Published:
Singapore :Springer Singapore : : 2022.,
Description:
xxii, 280 p. :ill. (chiefly col.), digital ;24 cm.
[NT 15003449]:
Logic driven traffic big data analytics: An introduction -- Statistical models and methods -- Spatial-temporal distribution model for travel origin-destination based on multi-source data -- Analyzing spatiotemporal congestion pattern on urban roads based on taxi GPS data -- A ride-sourcing group prediction model based on convolutional neural network.
Contained By:
Springer Nature eBook
Subject:
Traffic surveys - Data processing. -
Online resource:
https://doi.org/10.1007/978-981-16-8016-8
ISBN:
9789811680168
Logic-driven traffic big data analytics = methodology and applications for planning /
Zhong, Shaopeng.
Logic-driven traffic big data analytics
methodology and applications for planning /[electronic resource] :by Shaopeng Zhong, Daniel (Jian) Sun. - Singapore :Springer Singapore :2022. - xxii, 280 p. :ill. (chiefly col.), digital ;24 cm.
Logic driven traffic big data analytics: An introduction -- Statistical models and methods -- Spatial-temporal distribution model for travel origin-destination based on multi-source data -- Analyzing spatiotemporal congestion pattern on urban roads based on taxi GPS data -- A ride-sourcing group prediction model based on convolutional neural network.
This book starts from the relationship between urban built environment and travel behavior and focuses on analyzing the origin of traffic phenomena behind the data through multi-source traffic big data, which makes the book unique and different from the previous data-driven traffic big data analysis literature. This book focuses on understanding, estimating, predicting, and optimizing mobility patterns. Readers can find multi-source traffic big data processing methods, related statistical analysis models, and practical case applications from this book. This book bridges the gap between traffic big data, statistical analysis models, and mobility pattern analysis with a systematic investigation of traffic big data's impact on mobility patterns and urban planning.
ISBN: 9789811680168
Standard No.: 10.1007/978-981-16-8016-8doiSubjects--Topical Terms:
3591808
Traffic surveys
--Data processing.
LC Class. No.: HE336.A8 / Z56 2022
Dewey Class. No.: 388.314
Logic-driven traffic big data analytics = methodology and applications for planning /
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Logic driven traffic big data analytics: An introduction -- Statistical models and methods -- Spatial-temporal distribution model for travel origin-destination based on multi-source data -- Analyzing spatiotemporal congestion pattern on urban roads based on taxi GPS data -- A ride-sourcing group prediction model based on convolutional neural network.
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This book starts from the relationship between urban built environment and travel behavior and focuses on analyzing the origin of traffic phenomena behind the data through multi-source traffic big data, which makes the book unique and different from the previous data-driven traffic big data analysis literature. This book focuses on understanding, estimating, predicting, and optimizing mobility patterns. Readers can find multi-source traffic big data processing methods, related statistical analysis models, and practical case applications from this book. This book bridges the gap between traffic big data, statistical analysis models, and mobility pattern analysis with a systematic investigation of traffic big data's impact on mobility patterns and urban planning.
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based on 0 review(s)
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W9438727
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EB HE336.A8 Z56 2022
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