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Author: Dieter Jungnickel Publisher: Springer Science & Business Media ISBN: 3662038226 Category : Mathematics Languages : en Pages : 597
Book Description
Revised throughout Includes new chapters on the network simplex algorithm and a section on the five color theorem Recent developments are discussed
Author: Dieter Jungnickel Publisher: Springer Science & Business Media ISBN: 3662038226 Category : Mathematics Languages : en Pages : 597
Book Description
Revised throughout Includes new chapters on the network simplex algorithm and a section on the five color theorem Recent developments are discussed
Author: Dieter Jungnickel Publisher: Springer Science & Business Media ISBN: 9783540219057 Category : Computers Languages : en Pages : 642
Book Description
"This thoroughly revised new edition offers a new chapter on the network simplex algorithm and a section on the five color theorem. Moreover, numerous smaller changes and corrections have been made and several recent developments have been discussed and referenced."--BOOK JACKET.Title Summary field provided by Blackwell North America, Inc. All Rights Reserved
Author: Dieter Jungnickel Publisher: Springer Science & Business Media ISBN: 3540269088 Category : Mathematics Languages : en Pages : 612
Book Description
Revised throughout Includes new chapters on the network simplex algorithm and a section on the five color theorem Recent developments are discussed
Author: S. R. Kingan Publisher: John Wiley & Sons ISBN: 1118937279 Category : Mathematics Languages : en Pages : 292
Book Description
Graphs and Networks A unique blend of graph theory and network science for mathematicians and data science professionals alike. Featuring topics such as minors, connectomes, trees, distance, spectral graph theory, similarity, centrality, small-world networks, scale-free networks, graph algorithms, Eulerian circuits, Hamiltonian cycles, coloring, higher connectivity, planar graphs, flows, matchings, and coverings, Graphs and Networks contains modern applications for graph theorists and a host of useful theorems for network scientists. The book begins with applications to biology and the social and political sciences and gradually takes a more theoretical direction toward graph structure theory and combinatorial optimization. A background in linear algebra, probability, and statistics provides the proper frame of reference. Graphs and Networks also features: Applications to neuroscience, climate science, and the social and political sciences A research outlook integrated directly into the narrative with ideas for students interested in pursuing research projects at all levels A large selection of primary and secondary sources for further reading Historical notes that hint at the passion and excitement behind the discoveries Practice problems that reinforce the concepts and encourage further investigation and independent work
Author: Mark Needham Publisher: "O'Reilly Media, Inc." ISBN: 1492047635 Category : Computers Languages : en Pages : 297
Book Description
Discover how graph algorithms can help you leverage the relationships within your data to develop more intelligent solutions and enhance your machine learning models. You’ll learn how graph analytics are uniquely suited to unfold complex structures and reveal difficult-to-find patterns lurking in your data. Whether you are trying to build dynamic network models or forecast real-world behavior, this book illustrates how graph algorithms deliver value—from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. This practical book walks you through hands-on examples of how to use graph algorithms in Apache Spark and Neo4j—two of the most common choices for graph analytics. Also included: sample code and tips for over 20 practical graph algorithms that cover optimal pathfinding, importance through centrality, and community detection. Learn how graph analytics vary from conventional statistical analysis Understand how classic graph algorithms work, and how they are applied Get guidance on which algorithms to use for different types of questions Explore algorithm examples with working code and sample datasets from Spark and Neo4j See how connected feature extraction can increase machine learning accuracy and precision Walk through creating an ML workflow for link prediction combining Neo4j and Spark
Author: K Erciyes Publisher: Springer ISBN: 3319732358 Category : Computers Languages : en Pages : 471
Book Description
This clearly structured textbook/reference presents a detailed and comprehensive review of the fundamental principles of sequential graph algorithms, approaches for NP-hard graph problems, and approximation algorithms and heuristics for such problems. The work also provides a comparative analysis of sequential, parallel and distributed graph algorithms – including algorithms for big data – and an investigation into the conversion principles between the three algorithmic methods. Topics and features: presents a comprehensive analysis of sequential graph algorithms; offers a unifying view by examining the same graph problem from each of the three paradigms of sequential, parallel and distributed algorithms; describes methods for the conversion between sequential, parallel and distributed graph algorithms; surveys methods for the analysis of large graphs and complex network applications; includes full implementation details for the problems presented throughout the text; provides additional supporting material at an accompanying website. This practical guide to the design and analysis of graph algorithms is ideal for advanced and graduate students of computer science, electrical and electronic engineering, and bioinformatics. The material covered will also be of value to any researcher familiar with the basics of discrete mathematics, graph theory and algorithms.
Author: Gabriel Valiente Publisher: Springer Science & Business Media ISBN: 366204921X Category : Computers Languages : en Pages : 492
Book Description
Graph algorithms is a well-established subject in mathematics and computer science. Beyond classical application fields, such as approximation, combinatorial optimization, graphics, and operations research, graph algorithms have recently attracted increased attention from computational molecular biology and computational chemistry. Centered around the fundamental issue of graph isomorphism, this text goes beyond classical graph problems of shortest paths, spanning trees, flows in networks, and matchings in bipartite graphs. Advanced algorithmic results and techniques of practical relevance are presented in a coherent and consolidated way. This book introduces graph algorithms on an intuitive basis followed by a detailed exposition in a literate programming style, with correctness proofs as well as worst-case analyses. Furthermore, full C++ implementations of all algorithms presented are given using the LEDA library of efficient data structures and algorithms.
Author: Kayhan Erciyes Publisher: Springer Science & Business Media ISBN: 1447151739 Category : Computers Languages : en Pages : 328
Book Description
This book presents a comprehensive review of key distributed graph algorithms for computer network applications, with a particular emphasis on practical implementation. Topics and features: introduces a range of fundamental graph algorithms, covering spanning trees, graph traversal algorithms, routing algorithms, and self-stabilization; reviews graph-theoretical distributed approximation algorithms with applications in ad hoc wireless networks; describes in detail the implementation of each algorithm, with extensive use of supporting examples, and discusses their concrete network applications; examines key graph-theoretical algorithm concepts, such as dominating sets, and parameters for mobility and energy levels of nodes in wireless ad hoc networks, and provides a contemporary survey of each topic; presents a simple simulator, developed to run distributed algorithms; provides practical exercises at the end of each chapter.
Author: Krishnaiyan "KT" Thulasiraman Publisher: CRC Press ISBN: 1420011073 Category : Computers Languages : en Pages : 1217
Book Description
The fusion between graph theory and combinatorial optimization has led to theoretically profound and practically useful algorithms, yet there is no book that currently covers both areas together. Handbook of Graph Theory, Combinatorial Optimization, and Algorithms is the first to present a unified, comprehensive treatment of both graph theory and c
Author: Dieter Jungnickel
Author: Dieter Jungnickel
Author: Dieter Jungnickel
Author: Dieter Jungnickel
Author: S. R. Kingan
Author: Mark Needham
Author: K Erciyes
Author: Gabriel Valiente
Author: Kayhan Erciyes
Author: Nirmal K. Bose
Author: Krishnaiyan "KT" Thulasiraman