Computation In Complex Networks

Author : Clara Pizzuti
Publisher : MDPI
ISBN 13 : 3036506829
Total Pages : 352 pages
Book Rating : 4.21/5 ( download)

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Download or read book Computation in Complex Networks written by Clara Pizzuti and published by MDPI. This book was released on 2021-09-02 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine

Author : Joseph T. Lizier
Publisher : Springer Science & Business Media
ISBN 13 : 3642329527
Total Pages : 249 pages
Book Rating : 4.24/5 ( download)

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Download or read book The Local Information Dynamics of Distributed Computation in Complex Systems written by Joseph T. Lizier and published by Springer Science & Business Media. This book was released on 2012-11-06 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nature of distributed computation in complex systems has often been described in terms of memory, communication and processing. This thesis presents a complete information-theoretic framework to quantify these operations on information (i.e. information storage, transfer and modification), and in particular their dynamics in space and time. The framework is applied to cellular automata, and delivers important insights into the fundamental nature of distributed computation and the dynamics of complex systems (e.g. that gliders are dominant information transfer agents). Applications to several important network models, including random Boolean networks, suggest that the capability for information storage and coherent transfer are maximised near the critical regime in certain order-chaos phase transitions. Further applications to study and design information structure in the contexts of computational neuroscience and guided self-organisation underline the practical utility of the techniques presented here.

Author : Clara Pizzuti
Publisher :
ISBN 13 : 9783036506838
Total Pages : 352 pages
Book Rating : 4.37/5 ( download)

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Download or read book Computation in Complex Networks written by Clara Pizzuti and published by . This book was released on 2021 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex networks are one of the most challenging research focuses of disciplines, including physics, mathematics, biology, medicine, engineering, and computer science, among others. The interest in complex networks is increasingly growing, due to their ability to model several daily life systems, such as technology networks, the Internet, and communication, chemical, neural, social, political and financial networks. The Special Issue “Computation in Complex Networks" of Entropy offers a multidisciplinary view on how some complex systems behave, providing a collection of original and high-quality papers within the research fields of: • Community detection • Complex network modelling • Complex network analysis • Node classification • Information spreading and control • Network robustness • Social networks • Network medicine.

Author : Jinhu Lü
Publisher : Springer
ISBN 13 : 3662478242
Total Pages : 482 pages
Book Rating : 4.40/5 ( download)

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Download or read book Complex Systems and Networks written by Jinhu Lü and published by Springer. This book was released on 2015-08-14 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: This elementary book provides some state-of-the-art research results on broad disciplinary sciences on complex networks. It presents an in-depth study with detailed description of dynamics, controls and applications of complex networks. The contents of this book can be summarized as follows. First, the dynamics of complex networks, for example, the cluster dynamic analysis by using kernel spectral methods, community detection algorithms in bipartite networks, epidemiological modeling with demographics and epidemic spreading on multi-layer networks, are studied. Second, the controls of complex networks are investigated including topics like distributed finite-time cooperative control of multi-agent systems by applying homogenous-degree and Lyapunov methods, composite finite-time containment control for disturbed second-order multi-agent systems, fractional-order observer design of multi-agent systems, chaos control and anticontrol of complex systems via Parrondos game and many more. Third, the applications of complex networks provide some applicable carriers, which show the importance of theories developed in complex networks. In particular, a general model for studying time evolution of transition networks, deflection routing in complex networks, recommender systems for social networks analysis and mining, strategy selection in networked evolutionary games, integration and methods in computational biology, are discussed in detail.

Author : Matthias Dehmer
Publisher : Springer Science & Business Media
ISBN 13 : 0817647899
Total Pages : 493 pages
Book Rating : 4.96/5 ( download)

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Download or read book Structural Analysis of Complex Networks written by Matthias Dehmer and published by Springer Science & Business Media. This book was released on 2010-10-14 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science, machine learning, artificial intelligence, computational and systems biology, cognitive science, computational linguistics, and mathematical chemistry. It may also be used as a supplementary textbook in graduate-level seminars on structural graph analysis, complex networks, or network-based machine learning methods.

Author : Hocine Cherifi
Publisher : Springer Nature
ISBN 13 : 3030366839
Total Pages : 1047 pages
Book Rating : 4.34/5 ( download)

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Download or read book Complex Networks and Their Applications VIII written by Hocine Cherifi and published by Springer Nature. This book was released on 2019-11-26 with total page 1047 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students, and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the Eighth International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2019), which took place in Lisbon, Portugal, on December 10–12, 2019. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, and network dynamics; diffusion, epidemics, and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and neuroscience networks; and technological networks.

Author : Harald Atmanspacher
Publisher : Springer Science & Business Media
ISBN 13 : 1489923055
Total Pages : 362 pages
Book Rating : 4.59/5 ( download)

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Download or read book Information Dynamics written by Harald Atmanspacher and published by Springer Science & Business Media. This book was released on 2013-11-11 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of a NATO ASI held in Irsee/Kaufbeuren, Germany, June 15--26, 1990

Author : Jing Liu
Publisher : Springer
ISBN 13 : 3319600001
Total Pages : 148 pages
Book Rating : 4.00/5 ( download)

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Download or read book Evolutionary Computation and Complex Networks written by Jing Liu and published by Springer. This book was released on 2018-09-22 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the linkage between evolutionary computation and complex networks and the advantages of cross-fertilising ideas from both fields. Instead of introducing each field individually, the authors focus on the research that sits at the interface of both fields. The book is structured to address two questions: (1) how complex networks are used to analyze and improve the performance of evolutionary computation methods? (2) how evolutionary computation methods are used to solve problems in complex networks? The authors interweave complex networks and evolutionary computing, using evolutionary computation to discover community structure, while also using network analysis techniques to analyze the performance of evolutionary algorithms. The book is suitable for both beginners and senior researchers in the fields of evolutionary computation and complex networks.

Author : Chantal Cherifi
Publisher : Springer
ISBN 13 : 331972150X
Total Pages : 1288 pages
Book Rating : 4.07/5 ( download)

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Download or read book Complex Networks & Their Applications VI written by Chantal Cherifi and published by Springer. This book was released on 2017-11-24 with total page 1288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the VI International Conference on Complex Networks and their Applications (COMPLEX NETWORKS 2017), which took place in Lyon on November 29 – December 1, 2017. The carefully selected papers cover a wide range of theoretical topics such as network models and measures; community structure, network dynamics; diffusion, epidemics and spreading processes; resilience and control as well as all the main network applications, including social and political networks; networks in finance and economics; biological and ecological networks and technological networks.

Author : Thiago Christiano Silva
Publisher : Springer
ISBN 13 : 3319172905
Total Pages : 331 pages
Book Rating : 4.03/5 ( download)

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Download or read book Machine Learning in Complex Networks written by Thiago Christiano Silva and published by Springer. This book was released on 2016-01-28 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the features and advantages offered by complex networks in the machine learning domain. In the first part, an overview on complex networks and network-based machine learning is presented, offering necessary background material. In the second part, we describe in details some specific techniques based on complex networks for supervised, non-supervised, and semi-supervised learning. Particularly, a stochastic particle competition technique for both non-supervised and semi-supervised learning using a stochastic nonlinear dynamical system is described in details. Moreover, an analytical analysis is supplied, which enables one to predict the behavior of the proposed technique. In addition, data reliability issues are explored in semi-supervised learning. Such matter has practical importance and is not often found in the literature. With the goal of validating these techniques for solving real problems, simulations on broadly accepted databases are conducted. Still in this book, we present a hybrid supervised classification technique that combines both low and high orders of learning. The low level term can be implemented by any classification technique, while the high level term is realized by the extraction of features of the underlying network constructed from the input data. Thus, the former classifies the test instances by their physical features, while the latter measures the compliance of the test instances with the pattern formation of the data. We show that the high level technique can realize classification according to the semantic meaning of the data. This book intends to combine two widely studied research areas, machine learning and complex networks, which in turn will generate broad interests to scientific community, mainly to computer science and engineering areas.