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Titlebook: Logic-Driven Traffic Big Data Analytics; Methodology and Appl Shaopeng Zhong,Daniel (Jian) Sun Book 2022 The Editor(s) (if applicable) and

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書(shū)目名稱(chēng)Logic-Driven Traffic Big Data Analytics
副標(biāo)題Methodology and Appl
編輯Shaopeng Zhong,Daniel (Jian) Sun
視頻videohttp://file.papertrans.cn/589/588113/588113.mp4
概述Provides a complete set of logic-driven traffic big data analysis method.Uses a wealth of practical cases to introduce the methods in this book.Bridges the gap between traffic big data, statistical an
圖書(shū)封面Titlebook: Logic-Driven Traffic Big Data Analytics; Methodology and Appl Shaopeng Zhong,Daniel (Jian) Sun Book 2022 The Editor(s) (if applicable) and
描述.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..
出版日期Book 2022
關(guān)鍵詞Transportation Planning; Urban Planning; Traffic Big Data; Built Environment and Travel Behavior; Machin
版次1
doihttps://doi.org/10.1007/978-981-16-8016-8
isbn_softcover978-981-16-8018-2
isbn_ebook978-981-16-8016-8
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Exploring the Spatially Heterogeneous Effects of Urban Built Environment on Road Travel Time Variabed on the results of the geographically weighted regression model, the spatially varying relationships between urban built environment and road travel time can be established, thus providing important information for decision-makers to reduce road travel time by adjusting the attributes of urban built environment.
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