Modern and Interdisciplinary Problems in Network Science : A Translational Research Perspective

Zengqiang Chen

ISBN 10: 0815376588 / ISBN 13: 9780815376583

Editore: Taylor & Francis Inc Sep 2018, 2018

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Dati bibliografici

• Titolo: Modern and Interdisciplinary Problems in Network Science : A Translational Research Perspective
• Editore: Taylor & Francis Inc Sep 2018
• Data di pubblicazione: 2018
• Lingua: Inglese
• ISBN 10: 0815376588
• ISBN 13: 9780815376583
• Rilegatura: Buch
• Condizione: Neu

Descrizione articolo

Riassunto

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.

Informazioni sull?autore

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.