Evolutionary Algorithms for Community Detection in Complex Networks
Author: Babak Amiri
Publisher:
Published: 2014
Total Pages:
ISBN-13:
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Evolutionary Computation and Complex Networks
Author: Jing Liu
Publisher: Springer
Published: 2018-09-22
Total Pages: 160
ISBN-13: 3319600001
DOWNLOAD EBOOKThis 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.
Parallel Problem Solving from Nature - PPSN X
Author: Günter Rudolph
Publisher: Springer Science & Business Media
Published: 2008-09-10
Total Pages: 1183
ISBN-13: 3540876995
DOWNLOAD EBOOKThis book constitutes the refereed proceedings of the 10th International Conference on Parallel Problem Solving from Nature, PPSN 2008, held in Dortmund, Germany, in September 2008. The 114 revised full papers presented were carefully reviewed and selected from 206 submissions. The conference covers a wide range of topics, such as evolutionary computation, quantum computation, molecular computation, neural computation, artificial life, swarm intelligence, artificial ant systems, artificial immune systems, self-organizing systems, emergent behaviors, and applications to real-world problems. The paper are organized in topical sections on formal theory, new techniques, experimental analysis, multiobjective optimization, hybrid methods, and applications.
Intelligent Methods and Big Data in Industrial Applications
Author: Robert Bembenik
Publisher: Springer
Published: 2018-05-18
Total Pages: 370
ISBN-13: 3319776045
DOWNLOAD EBOOKThe inspiration for this book came from the Industrial Session of the ISMIS 2017 Conference in Warsaw. It covers numerous applications of intelligent technologies in various branches of the industry. Intelligent computational methods and big data foster innovation and enable the industry to overcome technological limitations and explore the new frontiers. Therefore it is necessary for scientists and practitioners to cooperate and inspire each other, and use the latest research findings to create new designs and products. As such, the contributions cover solutions to the problems experienced by practitioners in the areas of artificial intelligence, complex systems, data mining, medical applications and bioinformatics, as well as multimedia- and text processing. Further, the book shows new directions for cooperation between science and industry and facilitates efficient transfer of knowledge in the area of intelligent information systems.
Modern Graph Theory
Author: Bela Bollobas
Publisher: Springer Science & Business Media
Published: 2013-12-01
Total Pages: 408
ISBN-13: 1461206197
DOWNLOAD EBOOKAn in-depth account of graph theory, written for serious students of mathematics and computer science. It reflects the current state of the subject and emphasises connections with other branches of pure mathematics. Recognising that graph theory is one of several courses competing for the attention of a student, the book contains extensive descriptive passages designed to convey the flavour of the subject and to arouse interest. In addition to a modern treatment of the classical areas of graph theory, the book presents a detailed account of newer topics, including Szemerédis Regularity Lemma and its use, Shelahs extension of the Hales-Jewett Theorem, the precise nature of the phase transition in a random graph process, the connection between electrical networks and random walks on graphs, and the Tutte polynomial and its cousins in knot theory. Moreover, the book contains over 600 well thought-out exercises: although some are straightforward, most are substantial, and some will stretch even the most able reader.
Community Detection in Complex Networks Using Evolutionary Computation
Author: Guanbo Jia
Publisher:
Published: 2016
Total Pages: 0
ISBN-13:
DOWNLOAD EBOOKCellular Learning Automata: Theory and Applications
Author: Reza Vafashoar
Publisher: Springer Nature
Published: 2020-07-24
Total Pages: 377
ISBN-13: 3030531414
DOWNLOAD EBOOKThis book highlights both theoretical and applied advances in cellular learning automata (CLA), a type of hybrid computational model that has been successfully employed in various areas to solve complex problems and to model, learn, or simulate complicated patterns of behavior. Owing to CLA’s parallel and learning abilities, it has proven to be quite effective in uncertain, time-varying, decentralized, and distributed environments. The book begins with a brief introduction to various CLA models, before focusing on recently developed CLA variants. In turn, the research areas related to CLA are addressed as bibliometric network analysis perspectives. The next part of the book presents CLA-based solutions to several computer science problems in e.g. static optimization, dynamic optimization, wireless networks, mesh networks, and cloud computing. Given its scope, the book is well suited for all researchers in the fields of artificial intelligence and reinforcement learning.
Computation in Complex Networks
Author: Clara Pizzuti
Publisher: MDPI
Published: 2021-09-02
Total Pages: 352
ISBN-13: 3036506829
DOWNLOAD EBOOKComplex 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
Structure and Evolution
Author: Binxing Fang
Publisher: Walter de Gruyter GmbH & Co KG
Published: 2019-08-05
Total Pages: 163
ISBN-13: 3110598078
DOWNLOAD EBOOKThe three volume set provides a systematic overview of theories and technique on social network analysis. Volume 1 of the set mainly focuses on the structure characteristics, the modeling, and the evolution mechanism of social network analysis. Techniques and approaches for virtual community detection are discussed in detail as well. It is an essential reference for scientist and professionals in computer science.
Representations for Genetic and Evolutionary Algorithms
Author: Franz Rothlauf
Publisher: Physica
Published: 2012-12-06
Total Pages: 295
ISBN-13: 3642880940
DOWNLOAD EBOOKIn the field of genetic and evolutionary algorithms (GEAs), much theory and empirical study has been heaped upon operators and test problems, but problem representation has often been taken as given. This monograph breaks with this tradition and studies a number of critical elements of a theory of representations for GEAs and applies them to the empirical study of various important idealized test functions and problems of commercial import. The book considers basic concepts of representations, such as redundancy, scaling and locality and describes how GEAs'performance is influenced. Using the developed theory representations can be analyzed and designed in a theory-guided manner. The theoretical concepts are used as examples for efficiently solving integer optimization problems and network design problems. The results show that proper representations are crucial for GEAs'success.
