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000845766 019__ $$a1050336855
000845766 020__ $$a9783319962474$$q(electronic book)
000845766 020__ $$a3319962477$$q(electronic book)
000845766 020__ $$z9783319962467
000845766 020__ $$z3319962469
000845766 035__ $$aSP(OCoLC)on1050110405
000845766 035__ $$aSP(OCoLC)1050110405$$z(OCoLC)1050336855
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000845766 049__ $$aISEA
000845766 050_4 $$aT57.85$$b.I683 2017
000845766 08204 $$a003/.72$$223
000845766 1112_ $$aInternational Conference on Network Analysis$$n(7th :$$d2017 :$$cNizhniĭ Novgorod, Russia)
000845766 24510 $$aComputational Aspects and Applications in Large-Scale Networks :$$bNET 2017, Nizhny Novgorod, Russia, June 2017 /$$cValery A. Kalyagin,  Panos M. Pardalos, Oleg Prokopyev, Irina Utkina, editors.
000845766 264_1 $$aCham, Switzerland :$$bSpringer,$$c[2018]
000845766 300__ $$a1 online resource.
000845766 336__ $$atext$$btxt$$2rdacontent
000845766 337__ $$acomputer$$bc$$2rdamedia
000845766 338__ $$aonline resource$$bcr$$2rdacarrier
000845766 4901_ $$aSpringer proceedings in mathematics & statistics,$$x2194-1009 ;$$vvoume 247
000845766 504__ $$aIncludes bibliographical references.
000845766 5050_ $$aIntro; Preface; References; Contents; Contributors; Network Computational Algorithms; Tabu Search for Fleet Size and Mix Vehicle Routing Problem with Hard and Soft Time Windows; 1 Introduction; 2 Mathematical Model; 3 Algorithm Description; 3.1 Initial Solution; 3.2 Solution Improvement; 4 Computational Experiments; 4.1 VRPTW Results Comparison; 4.2 Results for FSMVRPSTW; 5 Conclusion; References; FPT Algorithms for the Shortest Lattice Vector and Integer Linear Programming Problems; 1 Introduction; 2 FPT Algorithm for the SVP; 3 The SVP for a Special Class of Lattices
000845766 5058_ $$a4 Integer Linear Programming Problem (ILPP)5 Conclusion; References; The Video-Based Age and Gender Recognition with Convolution Neural Networks; 1 Introduction; 2 Materials and Methods; 2.1 Literature Survey; 2.2 Proposed Algorithm; 3 Experimental Results and Discussion; 4 Conclusion and Future Work; References; On Forbidden Induced Subgraphs for the Class of Triangle-König Graphs; 1 Introduction; 2 Notation and Definitions; 3 The Simplest Minimal Forbidden Induced Subgraph; 4 Belts; 5 Rings; 6 Common Theorem; References
000845766 5058_ $$aThe Global Search Theory Approach to the Bilevel Pricing Problem in Telecommunication Networks1 Introduction; 2 Problem Statement and Reduction; 3 Special Local Search Method; 4 Global Search; 5 Implementation of the GSA; 6 Case Study; 7 Concluding Remarks; References; Graph Dichotomy Algorithm and Its Applications to Analysis of Stocks Market; 1 Introduction; 2 Dichotomy Complexity of Graph; 2.1 Frequency Dichotomy Algorithm; 2.2 Family of Dichotomies and Its Properties; 3 Stock Market Analysis; 3.1 Everyday Complexity Values for SampP-500; 3.2 Short-Term Prediction of Big Crises
000845766 5058_ $$a4 ConclusionReferences; Cluster Analysis of Facial Video Data in Video Surveillance Systems Using Deep Learning; 1 Introduction; 2 Cluster Analysis in Video Data; 3 Experimental Results; 4 Conclusion; References; Using Modular Decomposition Technique to Solve the Maximum Clique Problem; 1 Introduction; 2 Modular Decomposition Algorithm; 3 The Maximum Clique Solver Based on the Modular Decomposition Tree; 4 Results on DIMACS Benchmarks; 5 Algorithms for Generating Graphs with Modules; 5.1 Graphs of Mutual Simplicity; 5.2 Co-Graphs; 6 Results on Generated Graphs
000845766 5058_ $$a6.1 Graphs of Mutual Simplicity6.2 Co-Graphs; 7 Conclusion; References; Network Models; Robust Statistical Procedures for Testing Dynamics in Market Network; 1 Introduction; 2 Methodology; 3 Experimental Results; 4 Rejection Graph; 5 Concluding Remarks; References; Application of Market Models to Network Equilibrium Problems; 1 Introduction; 2 A General Multi-commodity Market Equilibrium Model; 3 Partial Linearization Methods; 4 A Generalization of Network Equilibrium Problems with Elastic Demands
000845766 506__ $$aAccess limited to authorized users.
000845766 520__ $$a"Contributions in this volume focus on computationally efficient algorithms and rigorous mathematical theories for analyzing large-scale networks. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis. Computational aspects and applications of large-scale networks in market models, neural networks, social networks, power transmission grids, maximum clique problem, telecommunication networks, and complexity graphs are included with new tools for efficient network analysis of large-scale networks. This proceeding is a result of the 7th International Conference in Network Analysis, held at the Higher School of Economics, Nizhny Novgorod in June 2017. The conference brought together scientists, engineers, and researchers from academia, industry, and government."--$$cProvided by publisher.
000845766 588__ $$aDescription based on online resource; title from digital title page (viewed on September 14, 2018).
000845766 650_0 $$aNetwork analysis (Planning)$$vCongresses.
000845766 650_0 $$aLarge scale systems$$vCongresses.
000845766 655_7 $$aConference papers and proceedings.$$2lcgft
000845766 7001_ $$aKalyagin, Valery A.,$$eeditor.
000845766 77608 $$iPrint version: $$z3319962469$$z9783319962467$$w(OCoLC)1040657020
000845766 830_0 $$aSpringer proceedings in mathematics & statistics ;$$vv. 247.
000845766 852__ $$bebk
000845766 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-96247-4$$zOnline Access$$91397441.1
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000845766 983__ $$aOnline
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