Handbook of Mobility Data Mining, Volume 2

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Sprache: Englisch

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Beschreibung

Handbook of Mobility Data Mining, Volume Two: Mobility Analytics and Prediction introduces the fundamental technologies of mobile big data mining (MDM), advanced AI methods, and upper-level applications, helping readers comprehensively understand MDM with a bottom-up approach. The book explains how to preprocess mobile big data, visualize urban mobility, simulate and predict human travel behavior, and assess urban mobility characteristics and their matching performance as conditions and constraints in transport, emergency management, and sustainability development systems. The book introduces how to design MDM platforms that adapt to the evolving mobility environment and new types of transportation and users.

This helpful guide provides a basis for how to simulate and predict mobility data. After an introductory theory chapter, the book then covers crucial topics such as long-term mobility pattern analytics, mobility data generators, user information inference, Grid-based population density prediction, and more. The book concludes with a chapter on graph-based mobility data analytics. The information in this work is crucial for researchers, engineers, operators, company administrators, and policymakers in related fields, to comprehensively understand current technologies' infra-knowledge structure and limitations.

Inhaltsverzeichnis

1. Mobility Simulation and Prediction: Concept, Theory, and Framework
2. Long-term Mobility Pattern Analytics-Changes Detection
3. Long-term Mobility Pattern Analytics-Clustering
4. Mobility Data Generator- Physical Models
5. Mobility Data Generator- Probabilistic Models
6. User Information Inference
7. Mobility Similarity Evaluation
8. Grid-based Population Density Prediction
9. Grid-based OD Prediction
10. Individual Trajectory Prediction
11. Graph-based Mobility Data Analytics

Details

Erscheinungsjahr:	2023
Medium:	Taschenbuch
Inhalt:	Einband - flex.(Paperback)
ISBN-13:	9780443184246
ISBN-10:	0443184240
Sprache:	Englisch
Herstellernummer:	C2022-0-00234-8
Einband:	Kartoniert / Broschiert
Redaktion:	Zhang, Haoran
Hersteller:	Elsevier Elsevier Science & Technology
Verantwortliche Person für die EU:	preigu GmbH & Co. KG, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de
Maße:	10 x 152 x 229 mm
Von/Mit:	Haoran Zhang
Erscheinungsdatum:	27.01.2023
Gewicht:	0,351 kg