Modern and Interdisciplinary Problems in Network Science

A Translational Research Perspective
1. Auflage 2020
ISBN: 978-0-367-65706-2
Verlag: Taylor & Francis Ltd

Buch, Englisch, 300 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 553 g

Modern and Interdisciplinary Problems in Network Science: A Translational Research Perspective covers a broad range of concepts and methods, with a strong emphasis on interdisciplinarity. The topics range from analyzing mathematical properties of network-based methods to applying them to application areas. By covering this broad range of topics, the book aims to fill a gap in the contemporary literature in disciplines such as physics, applied mathematics and information sciences.

Zielgruppe

Academic and Professional Practice & Development

Autoren/Hrsg.

Chen, Zengqiang

Dehmer, Matthias

Emmert-Streib, Frank

Shi, Yongtang

Fachgebiete

• Mathematik | Informatik Mathematik Mathematik Allgemein

Inhaltsverzeichnis

Chapter 1: The Spread of Strategies Predicted by Artificial Intelligence in Networks

Chunyan Zhang, Nankai University, China

Chapter 2: The Spread of Multiple Strategies in the Complex Networks

Jenlei Zhang, Nankai University, China

Chapter 3: The epidemic spreading processes in complex networks, Chengyi Xia, Tianjin University of Technology, China

Chapter 4: Measurements for Investigating complex networks

Z. Chen; Y. Shi; M. Dehmer; Nankai University, China, Austria

Chapter 5: Overview of Social Media Content and Network Analysis Mohammed Ali Al-Garadi, University of Malaya, Kuala Lumpur, Malaysia

Chapter 6: Analysis of Critical Infrastructure Network

David Rehak, University of Ostrava, CZ

Chapter 7: Evolving Networks and their Vulnerabilities,

Abbe Mowshowitz, New York City College, USA

Chapter 8: Review of structures and dynamics of economic complex networks: Large scale payment network of Estonia

Stephanie Rendón de la Torre, Tallinn University of Technology, Estonia

Chapter 9: Predicting Macroeconomic Variables using Financial Networks Properties

Petre Caraiani, Institute for Economic Forecasting, Romanian Academy, Romania

Chapter 10: Anomaly Detection in Complex Networks

Yaser Yasami, Department of Computer Engineering, Payame Noor University (PNU), Tehran, Iran

Chapter 11: Finding Justice through Network Analysis

Radboud Winkels, PPLE College Amsterdam, Holland,

Über Autor(innen)

Zengqiang Chen works at the Department of Automation at Nankai University, where he is currently a professor. His research interests are in complex networks, multi-agent systems, computer application systems, nonlinear dynamic control, intelligent computing and stochastic analysis.

Matthias Dehmer is a professor at University of Applied Sciences Upper Austria and UMIT - The Health and Life Sciences University. He also holds a guest professorship at Nankai University. His research interests are in graph theory, complex networks, complexity, machine big data, analytics, and information theory. In particular, he is also working on machine learning-based methods to design new data analysis methods for solving problems in manufacturing and production.

Frank Emmert-Streib is a professor at Tampere University Technology, Finland, in the Department of Signal Processing. His research interests are in the field of computational biology, data science and analytics in the development and application of methods from statistics and machine learning for the analysis of big data from genomics, finance and business.

Yongtang Shi is a professor at the Center for Combinatorics of Nankai University. His research interests are in graph theory and its applications, especially the applications of graph theory in mathematical chemistry, computer science and information theory.