
Handbook of Mobility Data Mining, Volume 2
Mobility Analytics and Prediction
Haoran Zhang(Editor)
Elsevier (Publisher)
Published on 27. January 2023
Book
Paperback/Softback
210 pages
978-0-443-18424-6 (ISBN)
Description
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.
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.
More details
Language
English
Place of publication
Philadelphia
United States
Target group
Professional and scholarly
Researchers, engineers, operators, company administrators, and policymakers on transportation, environment, urban planning, data mining, and sustainability
Transport-mobility planners, the road and vehicle industry, urban management authorities, transportation institutes, traffic police, public and goods transport operators; masters and Ph.D. students pursuing research in the area of mobility and transportation
Dimensions
Height: 229 mm
Width: 152 mm
Weight
450 gr
ISBN-13
978-0-443-18424-6 (9780443184246)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

E-Book
01/2023
Elsevier
€109.00
Available for download
Person
Haoran (Ronan) Zhang is Assistant Professor in the Center for Spatial Information Science at the University of Tokyo, a Researcher at the School of Business Society and Engineering at Maelardalen University in Sweden, and Senior Scientist at Locationmind Inc. in Japan. His research includes smart supply chain technologies, GPS data in shared transportation, urban sustainable performance, GIS technologies in renewable energy systems, and smart cities. He is author of numerous journal articles and Editorial Board Member of several international academic journals. He has Ph.D.'s in both Engineering and Sociocultural Environment and was awarded Excellent Young Researcher by Japan's Ministry of Education, Culture, Sports, Science and Technology.
Editor
Assistant Professor, Center for Spatial Information Science, University of Tokyo, Tokyo, Japan; Researcher, School of Business Society and Engineering, Maelardalen University, Sweden; Senior Scientist, Locationmind Inc., Tokyo, Japan
Content
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
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