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Titlebook: Urban Informatics Using Mobile Network Data; Travel Behavior Rese Santi Phithakkitnukoon Book 2023 The Editor(s) (if applicable) and The Au

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發(fā)表于 2025-3-23 10:25:23 | 只看該作者
Book 2023ere approaches, models, and systems are developed for understanding travel behavior. The objectives of this book are thus to evaluate the extent to which mobile network data reflects travel behavior and to develop guidelines on how to best use such data to understand and model travel behavior. To ac
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發(fā)表于 2025-3-23 17:50:50 | 只看該作者
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發(fā)表于 2025-3-23 19:40:13 | 只看該作者
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發(fā)表于 2025-3-23 23:16:20 | 只看該作者
Santi Phithakkitnukoonetransformation of this religion, and in particular in which context an individual can change the content of religion, and bring about new ideas regarding religion and belief..978-981-15-2637-4978-981-15-2635-0
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發(fā)表于 2025-3-24 02:30:40 | 只看該作者
ion. Mobile network data thus emerges as a promising alternative data source that is massive in both cross-sectional and longitudinal perspectives, and one that provides both broader geographic coverage of trav978-981-19-6716-0978-981-19-6714-6
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發(fā)表于 2025-3-24 08:51:49 | 只看該作者
The Overview of Mobile Network Data-Driven Urban Informatics,new opportunities as well as challenges in utilizing such data in travel behavior research. This chapter discusses the state of the art and outlines the rest of the book, which is a series of case studies done by our research teams based on mobile phone data collected from different countries to tac
17#
發(fā)表于 2025-3-24 13:32:12 | 只看該作者
Inferring Passenger Travel Demand Using Mobile Phone CDR Data,us identify trends in passenger demand so that better informed decisions about future investments in infrastructure and capacity can be made. In this chapter, we discuss how passenger demand for public transportation services can be estimated using mobile phone network data. Based on the inferred tr
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發(fā)表于 2025-3-24 18:40:04 | 只看該作者
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發(fā)表于 2025-3-24 22:42:33 | 只看該作者
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發(fā)表于 2025-3-25 02:32:36 | 只看該作者
Inferring Social Influence in Transport Mode Choice Using Mobile Phone CDR Data,is the person’s preferred mode of transportation. The data also shows that social ties that are geographically nearby have a greater influence on commuting mode choice than those that are farther away. In the case of public transportation, accessibility distance is also a deciding factor. As the acc
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