Large Scale Structure And Dynamics Of Complex Networks: From Information Technology To Finance And Natural Science PDF Download
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Author: Alessandro Vespignani
Publisher: World Scientific
ISBN: 9814475416
Category : Computers
Languages : en
Pages : 264
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Book Description
This book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters form a reference for the various problems in data analysis visualization and modeling of complex networks.
Author: Subhankar Dhar
Publisher: Academic Publishers
ISBN: 9383420723
Category : Computers
Languages : en
Pages : 100
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Book Description
Workshop Proceedings, Indian Statistical Institute, Kolkata December 19-20, 2015
Author: Alessandro Vespignani
Publisher: World Scientific
ISBN: 9814475416
Category : Computers
Languages : en
Pages : 264
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Book Description
This book is the culmination of three years of research effort on a multidisciplinary project in which physicists, mathematicians, computer scientists and social scientists worked together to arrive at a unifying picture of complex networks. The contributed chapters form a reference for the various problems in data analysis visualization and modeling of complex networks.
Author: Meghanathan, Natarajan
Publisher: IGI Global
ISBN: 1466699655
Category : Computers
Languages : en
Pages : 484
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Book Description
As network science and technology continues to gain popularity, it becomes imperative to develop procedures to examine emergent network domains, as well as classical networks, to help ensure their overall optimization. Advanced Methods for Complex Network Analysis features the latest research on the algorithms and analysis measures being employed in the field of network science. Highlighting the application of graph models, advanced computation, and analytical procedures, this publication is a pivotal resource for students, faculty, industry practitioners, and business professionals interested in theoretical concepts and current developments in network domains.
Author: Kihong Park
Publisher: Oxford University Press, USA
ISBN:
Category : Computers
Languages : en
Pages : 326
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Book Description
This volume contains a snapshot of some features of the Internet that may be fruitfully approached using a complex systems perspective, meaning using interdisciplinary tools and methods to tackle the subject area.
Author: Matthias Dehmer
Publisher: John Wiley & Sons
ISBN: 3527694374
Category : Medical
Languages : en
Pages : 368
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Book Description
This new title in the well-established "Quantitative Network Biology" series includes innovative and existing methods for analyzing network data in such areas as network biology and chemoinformatics. With its easy-to-follow introduction to the theoretical background and application-oriented chapters, the book demonstrates that R is a powerful language for statistically analyzing networks and for solving such large-scale phenomena as network sampling and bootstrapping. Written by editors and authors with an excellent track record in the field, this is the ultimate reference for R in Network Analysis.
Author: Matthias Dehmer
Publisher: CRC Press
ISBN: 1315353598
Category : Computers
Languages : en
Pages : 290
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Book Description
Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural data sets, including both very large networks and sets of graphs. As well as applying statistical analysis techniques like sampling and bootstrapping in an interdisciplinary manner to produce novel techniques for analyzing massive amounts of data, this book also explores the possibilities offered by the special aspects such as computer memory in investigating large sets of complex networks. Intended for computer scientists, statisticians and mathematicians interested in the big data and networks, Big Data of Complex Networks is also a valuable tool for researchers in the fields of visualization, data analysis, computer vision and bioinformatics. Key features: Provides a complete discussion of both the hardware and software used to organize big data Describes a wide range of useful applications for managing big data and resultant data sets Maintains a firm focus on massive data and large networks Unveils innovative techniques to help readers handle big data Matthias Dehmer received his PhD in computer science from the Darmstadt University of Technology, Germany. Currently, he is Professor at UMIT – The Health and Life Sciences University, Austria, and the Universität der Bundeswehr München. His research interests are in graph theory, data science, complex networks, complexity, statistics and information theory. Frank Emmert-Streib received his PhD in theoretical physics from the University of Bremen, and is currently Associate professor at Tampere University of Technology, Finland. His research interests are in the field of computational biology, machine learning and network medicine. Stefan Pickl holds a PhD in mathematics from the Darmstadt University of Technology, and is currently a Professor at Bundeswehr Universität München. His research interests are in operations research, systems biology, graph theory and discrete optimization. Andreas Holzinger received his PhD in cognitive science from Graz University and his habilitation (second PhD) in computer science from Graz University of Technology. He is head of the Holzinger Group HCI-KDD at the Medical University Graz and Visiting Professor for Machine Learning in Health Informatics Vienna University of Technology.
Author: Dmitry Zinoviev
Publisher: Pragmatic Bookshelf
ISBN: 1680505408
Category : Computers
Languages : en
Pages : 330
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Book Description
Construct, analyze, and visualize networks with networkx, a Python language module. Network analysis is a powerful tool you can apply to a multitude of datasets and situations. Discover how to work with all kinds of networks, including social, product, temporal, spatial, and semantic networks. Convert almost any real-world data into a complex network--such as recommendations on co-using cosmetic products, muddy hedge fund connections, and online friendships. Analyze and visualize the network, and make business decisions based on your analysis. If you're a curious Python programmer, a data scientist, or a CNA specialist interested in mechanizing mundane tasks, you'll increase your productivity exponentially. Complex network analysis used to be done by hand or with non-programmable network analysis tools, but not anymore! You can now automate and program these tasks in Python. Complex networks are collections of connected items, words, concepts, or people. By exploring their structure and individual elements, we can learn about their meaning, evolution, and resilience. Starting with simple networks, convert real-life and synthetic network graphs into networkx data structures. Look at more sophisticated networks and learn more powerful machinery to handle centrality calculation, blockmodeling, and clique and community detection. Get familiar with presentation-quality network visualization tools, both programmable and interactive--such as Gephi, a CNA explorer. Adapt the patterns from the case studies to your problems. Explore big networks with NetworKit, a high-performance networkx substitute. Each part in the book gives you an overview of a class of networks, includes a practical study of networkx functions and techniques, and concludes with case studies from various fields, including social networking, anthropology, marketing, and sports analytics. Combine your CNA and Python programming skills to become a better network analyst, a more accomplished data scientist, and a more versatile programmer. What You Need: You will need a Python 3.x installation with the following additional modules: Pandas (>=0.18), NumPy (>=1.10), matplotlib (>=1.5), networkx (>=1.11), python-louvain (>=0.5), NetworKit (>=3.6), and generalizesimilarity. We recommend using the Anaconda distribution that comes with all these modules, except for python-louvain, NetworKit, and generalizedsimilarity, and works on all major modern operating systems.
Author: Alex Fornito
Publisher: Academic Press
ISBN: 0124081185
Category : Medical
Languages : en
Pages : 496
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Book Description
Fundamentals of Brain Network Analysis is a comprehensive and accessible introduction to methods for unraveling the extraordinary complexity of neuronal connectivity. From the perspective of graph theory and network science, this book introduces, motivates and explains techniques for modeling brain networks as graphs of nodes connected by edges, and covers a diverse array of measures for quantifying their topological and spatial organization. It builds intuition for key concepts and methods by illustrating how they can be practically applied in diverse areas of neuroscience, ranging from the analysis of synaptic networks in the nematode worm to the characterization of large-scale human brain networks constructed with magnetic resonance imaging. This text is ideally suited to neuroscientists wanting to develop expertise in the rapidly developing field of neural connectomics, and to physical and computational scientists wanting to understand how these quantitative methods can be used to understand brain organization. - Winner of the 2017 PROSE Award in Biomedicine & Neuroscience and the 2017 British Medical Association (BMA) Award in Neurology - Extensively illustrated throughout by graphical representations of key mathematical concepts and their practical applications to analyses of nervous systems - Comprehensively covers graph theoretical analyses of structural and functional brain networks, from microscopic to macroscopic scales, using examples based on a wide variety of experimental methods in neuroscience - Designed to inform and empower scientists at all levels of experience, and from any specialist background, wanting to use modern methods of network science to understand the organization of the brain
Author: Yu-Chu Tian
Publisher: Springer Nature
ISBN: 981995648X
Category : Technology & Engineering
Languages : en
Pages : 578
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Book Description
This book covers network analysis and architecture for large-scale computer network planning. Networks and the Internet are essential for modern industries and societies. Building a new network, upgrading an existing network, or planning to use a public network requires integrating various network mechanisms and technologies in a cohesive fashion. This demands a deep understanding of the concepts, principles, processes, approaches, and good practices of advanced network planning. More specifically, emphasizing service-based networking, the book introduces structured processes for network planning, provides systematic approaches for network analysis and architecture, develops network planning specifications, and discusses high-level network architectural models from various perspectives. It also offers detailed discussions on component-based architecture about addressing, routing, performance, management, and security and privacy. Recent developments in data centers, virtualization, and cloud are also embedded into the network architecture. Moreover, the book includes a comprehensive introduction to building practical TCP/IP network communications via sockets with practical examples. The book is suitable for use as a textbook for senior undergraduate and postgraduate students or as a reference book for network practitioners looking to develop or enhance their skills in network planning.
Author: C.-H. Chen
Publisher: IOS Press
ISBN: 1643682555
Category : Computers
Languages : en
Pages : 1154
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Book Description
The pervasiveness of computers in every field of science, industry and everyday life has meant that applied mathematics, particularly in relation to modeling and simulation, has become ever more important in recent years. This book presents the proceedings of the 2021 International Conference on Applied Mathematics, Modeling and Computer Simulation (AMMCS 2021), hosted in Wuhan, China, and held as a virtual event from 13 to 14 November 2021. The aim of the conference is to foster the knowledge and understanding of recent advances across the broad fields of applied mathematics, modeling and computer simulation, and it provides an annual platform for scholars and researchers to communicate important recent developments in their areas of specialization to colleagues and other scientists in related disciplines. This year more than 150 participants were able to exchange knowledge and discuss recent developments via the conference. The book contains 115 peer-reviewed papers, selected from more than 250 submissions and ranging from the theoretical and conceptual to the strongly pragmatic and all addressing industrial best practice. Topics covered include mathematical modeling and applications, engineering applications and scientific computations, and the simulation of intelligent systems. Providing an overview of recent development and with a mix of practical experiences and enlightening ideas, the book will be of interest to researchers and practitioners everywhere.
