Algorithmics Of Large And Complex Networks PDF Download
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Author | : Jürgen Lerner |
Publisher | : Springer |
Total Pages | : 411 |
Release | : 2009-06-29 |
Genre | : Computers |
ISBN | : 3642020941 |
Download Algorithmics of Large and Complex Networks Book in PDF, ePub and Kindle
Networks play a central role in today’s society, since many sectors employing information technology, such as communication, mobility, and transport - even social interactions and political activities - are based on and rely on networks. In these times of globalization and the current global financial crisis with its complex and nearly incomprehensible entanglements of various structures and its huge effect on seemingly unrelated institutions and organizations, the need to understand large networks, their complex structures, and the processes governing them is becoming more and more important. This state-of-the-art survey reports on the progress made in selected areas of this important and growing field, thus helping to analyze existing large and complex networks and to design new and more efficient algorithms for solving various problems on these networks since many of them have become so large and complex that classical algorithms are not sufficient anymore. This volume emerged from a research program funded by the German Research Foundation (DFG) consisting of projects focusing on the design of new discrete algorithms for large and complex networks. The 18 papers included in the volume present the results of projects realized within the program and survey related work. They have been grouped into four parts: network algorithms, traffic networks, communication networks, and network analysis and simulation.
Author | : Jürgen Lerner |
Publisher | : Springer Science & Business Media |
Total Pages | : 411 |
Release | : 2009-07-02 |
Genre | : Computers |
ISBN | : 3642020933 |
Download Algorithmics of Large and Complex Networks Book in PDF, ePub and Kindle
A state-of-the-art survey that reports on the progress made in selected areas of this important and growing field, aiding the analysis of existing networks and the design of new and more efficient algorithms for solving various problems on these networks.
Author | : Matthias Dehmer |
Publisher | : CRC Press |
Total Pages | : 332 |
Release | : 2016-08-19 |
Genre | : Computers |
ISBN | : 1498723624 |
Download Big Data of Complex Networks Book in PDF, ePub and Kindle
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 | : Vito Latora |
Publisher | : Cambridge University Press |
Total Pages | : 585 |
Release | : 2017-09-28 |
Genre | : Science |
ISBN | : 1108298680 |
Download Complex Networks Book in PDF, ePub and Kindle
Networks constitute the backbone of complex systems, from the human brain to computer communications, transport infrastructures to online social systems and metabolic reactions to financial markets. Characterising their structure improves our understanding of the physical, biological, economic and social phenomena that shape our world. Rigorous and thorough, this textbook presents a detailed overview of the new theory and methods of network science. Covering algorithms for graph exploration, node ranking and network generation, among others, the book allows students to experiment with network models and real-world data sets, providing them with a deep understanding of the basics of network theory and its practical applications. Systems of growing complexity are examined in detail, challenging students to increase their level of skill. An engaging presentation of the important principles of network science makes this the perfect reference for researchers and undergraduate and graduate students in physics, mathematics, engineering, biology, neuroscience and the social sciences.
Author | : João Gama |
Publisher | : Springer |
Total Pages | : 487 |
Release | : 2009-10-07 |
Genre | : Computers |
ISBN | : 3642047475 |
Download Discovery Science Book in PDF, ePub and Kindle
This book constitutes the refereed proceedings of the twelfth International Conference, on Discovery Science, DS 2009, held in Porto, Portugal, in October 2009. The 35 revised full papers presented were carefully selected from 92 papers. The scope of the conference includes the development and analysis of methods for automatic scientific knowledge discovery, machine learning, intelligent data analysis, theory of learning, as well as their applications.
Author | : Gustav Lindmark |
Publisher | : Linköping University Electronic Press |
Total Pages | : 36 |
Release | : 2018-09-05 |
Genre | : |
ISBN | : 9176852431 |
Download Methods and algorithms for control input placement in complex networks Book in PDF, ePub and Kindle
The control-theoretic notion of controllability captures the ability to guide a systems behavior toward a desired state with a suitable choice of inputs. Controllability of complex networks such as traffic networks, gene regulatory networks, power grids etc. brings many opportunities. It could for instance enable improved efficiency in the functioning of a network or lead to that entirely new applicative possibilities emerge. However, when control theory is applied to complex networks like these, several challenges arise. This thesis consider some of these challenges, in particular we investigate how control inputs should be placed in order to render a given network controllable at a minimum cost, taking as cost function either the number of control inputs or the energy that they must exert. We assume that each control input targets only one node (called a driver node) and is either unconstrained or unilateral. A unilateral control input is one that can assume either positive or negative values but not both. Motivated by the many applications where unilateral controls are common, we reformulate classical controllability results for this particular case into a more computationally-efficient form that enables a large scale analysis. We show that the unilateral controllability problem is to a high degree structural and derive theoretical lower bounds on the minimal number of unilateral control inputs from topological properties of the network, similar to the bounds that exists for the minimal number of unconstrained control inputs. Moreover, an algorithm is developed that constructs a near minimal number of control inputs for a given network. When evaluated on various categories of random networks as well as a number of real-world networks, the algorithm often achieves the theoretical lower bounds. A network can be controllable in theory but not in practice when completely unreasonable amounts of control energy are required to steer it in some direction. For unconstrained control inputs we show that the control energy depends on the time constants of the modes of the network, and that the closer the eigenvalues are to the imaginary axis of the complex plane, the less energy is required for control. We also investigate the problem of placing driver nodes such that the control energy requirements are minimized (assuming that theoretical controllability is not an issue). For the special case with networks having all purely imaginary eigenvalues, several constructive algorithms for driver node placement are developed. In order to understand what determines the control energy in the general case with arbitrary eigenvalues, we define two centrality measures for the nodes based on energy flow considerations: the first centrality reflects the network impact of a node and the second the ability to control it indirectly. It turns out that whether a node is suitable as driver node or not largely depends on these two qualities. By combining the centralities into node rankings we obtain driver node placements that significantly reduce the control energy requirements and thereby improve the “practical degree of controllability”.
Author | : Hocine Cherifi |
Publisher | : Springer |
Total Pages | : 833 |
Release | : 2016-11-25 |
Genre | : Technology & Engineering |
ISBN | : 3319509012 |
Download Complex Networks & Their Applications V Book in PDF, ePub and Kindle
This book highlights cutting-edge research in the field of network science, offering scientists, researchers and graduate students a unique opportunity to catch up on the latest advances in theory and a multitude of applications. It presents the peer-reviewed proceedings of the fifth International Workshop on Complex Networks & their Applications (COMPLEX NETWORKS 2016), which took place in Milan during the last week of November 2016. The carefully selected papers are divided into 11 sections reflecting the diversity and richness of research areas in the field. More specifically, the following topics are covered: Network models; Network measures; Community structure; Network dynamics; Diffusion, epidemics and spreading processes; Resilience and control; Network visualization; Social and political networks; Networks in finance and economics; Biological and ecological networks; and Network analysis.
Author | : Meghanathan, Natarajan |
Publisher | : IGI Global |
Total Pages | : 461 |
Release | : 2016-04-07 |
Genre | : Computers |
ISBN | : 1466699655 |
Download Advanced Methods for Complex Network Analysis Book in PDF, ePub and Kindle
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 | : M. Hadi Amini |
Publisher | : Springer Nature |
Total Pages | : 306 |
Release | : 2020-02-22 |
Genre | : Technology & Engineering |
ISBN | : 3030340945 |
Download Optimization, Learning, and Control for Interdependent Complex Networks Book in PDF, ePub and Kindle
This book focuses on a wide range of optimization, learning, and control algorithms for interdependent complex networks and their role in smart cities operation, smart energy systems, and intelligent transportation networks. It paves the way for researchers working on optimization, learning, and control spread over the fields of computer science, operation research, electrical engineering, civil engineering, and system engineering. This book also covers optimization algorithms for large-scale problems from theoretical foundations to real-world applications, learning-based methods to enable intelligence in smart cities, and control techniques to deal with the optimal and robust operation of complex systems. It further introduces novel algorithms for data analytics in large-scale interdependent complex networks. • Specifies the importance of efficient theoretical optimization and learning methods in dealing with emerging problems in the context of interdependent networks • Provides a comprehensive investigation of advance data analytics and machine learning algorithms for large-scale complex networks • Presents basics and mathematical foundations needed to enable efficient decision making and intelligence in interdependent complex networks M. Hadi Amini is an Assistant Professor at the School of Computing and Information Sciences at Florida International University (FIU). He is also the founding director of Sustainability, Optimization, and Learning for InterDependent networks laboratory (solid lab). He received his Ph.D. and M.Sc. from Carnegie Mellon University in 2019 and 2015 respectively. He also holds a doctoral degree in Computer Science and Technology. Prior to that, he received M.Sc. from Tarbiat Modares University in 2013, and the B.Sc. from Sharif University of Technology in 2011.
Author | : Clara Pizzuti |
Publisher | : MDPI |
Total Pages | : 352 |
Release | : 2021-09-02 |
Genre | : Technology & Engineering |
ISBN | : 3036506829 |
Download Computation in Complex Networks Book in PDF, ePub and Kindle
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