Search results for "Complex network"

showing 10 items of 131 documents

Complexity traits and synchrony of cryptocurrencies price dynamics

2021

AbstractIn this study, we characterized the dynamics and analyzed the degree of synchronization of the time series of daily closing prices and volumes in US$ of three cryptocurrencies, Bitcoin, Ethereum, and Litecoin, over the period September 1,2015–March 31, 2020. Time series were first mapped into a complex network by the horizontal visibility algorithm in order to revel the structure of their temporal characters and dynamics. Then, the synchrony of the time series was investigated to determine the possibility that the cryptocurrencies under study co-bubble simultaneously. Findings reveal similar complex structures for the three virtual currencies in terms of number and internal composit…

CryptocurrencyCryptocurrencyTime series0211 other engineering and technologies02 engineering and technologySynchronizationSettore SECS-P/06 - Economia ApplicataStability (probability)SynchronizationArticleSettore SECS-S/06 -Metodi Mat. dell'Economia e d. Scienze Attuariali e Finanz.Order (exchange)0202 electrical engineering electronic engineering information engineeringEconometricsC6PredictabilityC32D53Mathematics021103 operations researchSeries (mathematics)020208 electrical & electronic engineeringComplex networkVirtual currencyBITCOIN COMPLEX NETWORK ANALYSIS CRYPTOCURRENCY SYNCHRONIZATION TIME SERIESGeneral Economics Econometrics and FinanceComplex network analysisFinanceBitcoinDecisions in Economics and Finance
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Impact of the community structure on the dynamics of complex networks

2023

Networks are everywhere. We encounter them daily in our lives, through our social interactions, how we come up with decisions in our brain, to having phone calls, conducting financial transactions, and traveling from one place to another. Individual actions are influenced by their environment, which is, in turn, influenced by the network's topology. Notably, individuals may change their actions, ideas, or opinions to conform to the aspirations of a particular social group. In the same vein, the spread of a virus can take a certain course if the network's structure induces specific pathways for expansion. In such scenarios, communities substantially impact the evolution of the dynamics. They…

Diffusion[INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI]CommunautésRéseaux complexesCommunitiesComplex networksCentralityCentralitéTopologieInfluential nodesTopologyNœuds influents
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The small-world of 'Le Petit Prince': Revisiting the word frequency distribution

2016

[EN] Many complex systems are naturally described through graph theory, and different kinds of systems described as networks present certain important characteristics in common. One of these features is the so-called scale-free distribution for its node s connectivity, which means that the degree distribution for the network s nodes follows a power law. Scale-free networks are usually referred to as small-world because the average distance between their nodes do not scale linearly with the size of the network, but logarithmically. Here we present a mathematical analysis on linguistics: the word frequency effect for different translations of the Le Petit Prince in different languages. Compar…

Discrete mathematicsLinguistics and LanguageNode (networking)05 social sciencesComplex system050109 social psychologyScale (descriptive set theory)Graph theoryWord AssociationComplex networkDegree distribution050105 experimental psychologyLanguage and LinguisticsComputer Science ApplicationsWord lists by frequency0501 psychology and cognitive sciencesArithmeticMATEMATICA APLICADAInformation SystemsMathematics
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Inferring slowly-changing dynamic gene-regulatory networks

2015

Dynamic gene-regulatory networks are complex since the interaction patterns between their components mean that it is impossible to study parts of the network in separation. This holistic character of gene-regulatory networks poses a real challenge to any type of modelling. Graphical models are a class of models that connect the network with a conditional independence relationships between random variables. By interpreting these random variables as gene activities and the conditional independence relationships as functional non-relatedness, graphical models have been used to describe gene-regulatory networks. Whereas the literature has been focused on static networks, most time-course experi…

Dynamic network analysisL1 penalized inferenceComputer scienceT-LymphocytesGene regulatory networkgene regulatory networkMachine learningcomputer.software_genreBiochemistrygene-regulatory networksStructural Biologygraphical modelscomputer simulationT lymphocyteHumansGene Regulatory NetworkshumanGraphical modelMolecular Biologylymphocyte activationClass (computer programming)Models Statisticalalgorithmbusiness.industryResearchApplied Mathematicsstatistical modelStatistical modelComplex networkQuantitative Biology::GenomicsComputer Science ApplicationsComputingMethodologies_PATTERNRECOGNITIONConditional independencemicroarray analysisComputingMethodologies_GENERALArtificial intelligencebusinessmetabolismRandom variablecomputerAlgorithmsBMC Bioinformatics
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Feigenbaum graphs: a complex network perspective of chaos

2011

The recently formulated theory of horizontal visibility graphs transforms time series into graphs and allows the possibility of studying dynamical systems through the characterization of their associated networks. This method leads to a natural graph-theoretical description of nonlinear systems with qualities in the spirit of symbolic dynamics. We support our claim via the case study of the period-doubling and band-splitting attractor cascades that characterize unimodal maps. We provide a universal analytical description of this classic scenario in terms of the horizontal visibility graphs associated with the dynamics within the attractors, that we call Feigenbaum graphs, independent of map…

Dynamical systems theoryScienceSymbolic dynamicsFOS: Physical sciencesLyapunov exponentFixed pointBioinformatics01 natural sciences010305 fluids & plasmasStatistical Mechanicssymbols.namesake0103 physical sciencesAttractorEntropy (information theory)Statistical physics010306 general physicsChaotic SystemsCondensed-Matter PhysicsCondensed Matter - Statistical MechanicsPhysicsMultidisciplinaryStatistical Mechanics (cond-mat.stat-mech)Applied MathematicsPhysicsQRComplex SystemsComplex networkNonlinear Sciences - Chaotic DynamicsDegree distributionNonlinear DynamicssymbolsMedicineChaotic Dynamics (nlin.CD)MathematicsAlgorithmsResearch Article
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Seeking the Important Nodes of Complex Networks in Product R&D Team Based on Fuzzy AHP and TOPSIS

2013

Published version of article in the journal: Mathematical Problems in Engineering. Alo available from the publisher at: http://dx.doi.org/10.1155/2013/327592 Open Access How to seek the important nodes of complex networks in product research and development (R&D) team is particularly important for companies engaged in creativity and innovation. The previous literature mainly uses several single indicators to assess the node importance; this paper proposes a multiple attribute decision making model to tentatively solve these problems. Firstly, choose eight indicators as the evaluation criteria, four from centralization of complex networks: degree centrality, betweenness centrality, closeness…

EngineeringArticle SubjectHierarchy (mathematics)business.industrylcsh:MathematicsGeneral MathematicsGeneral EngineeringAnalytic hierarchy processTOPSISComplex networklcsh:QA1-939VDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Constraint (information theory)Betweenness centralitylcsh:TA1-2040VDP::Matematikk og Naturvitenskap: 400::Matematikk: 410::Anvendt matematikk: 413Artificial intelligencelcsh:Engineering (General). Civil engineering (General)businessCentralityDecision-making modelsMathematical Problems in Engineering
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Applying complexity science to air traffic management

2015

Versión aceptada obtenida del archivo digital en línea WestminsterResearch de la Universidad de Westminster. Complexity science is the multidisciplinary study of complex systems. Its marked network orientation lends itself well to transport contexts. Key features of complexity science are introduced and defined, with a specific focus on the application to air traffic management. An overview of complex network theory is presented, with examples of its corresponding metrics and multiple scales. Complexity science is starting to make important contributions to performance assessment and system design: selected, applied air traffic management case studies are explored. The important contexts of…

EngineeringEmergent behaviourStrategy and ManagementComplex systemL-SpaceTransportationManagement Monitoring Policy and LawEmergent behaviorPerformance assessmentPerformance measurementResilience (network)Transportation NetworksResilienceManagement sciencebusiness.industryAir traffic managementComplex network theoryComplex networkAir traffic controlSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)Complexity scienceUrban Rail TransitSystems designSocio-ecological systembusinessLaw
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Energy Recovery in Water Distribution Networks. Implementation of Pumps as Turbine in a Dynamic Numerical Model

2014

In complex networks characterized by the presence of private tanks, water managers usually apply intermittent distribution, thus reducing the water volumes supplied to the users, or use Pressure Reduction Valves (PRV) for controlling pressure in the network. The application of Pump As Turbines (PATs) appears as an alternative and sustainable solution to either control network pressure as well as to produce energy. In the present paper, the hydrodynamic model, already presented by De Marchis et al. (2011) was further developed introducing the dynamic analysis of PATs. The model was applied to a district of Palermo network (Italy) characterized by intermittent distribution and by inequities a…

EngineeringEnergy recoveryDistribution networksPetroleum engineeringbusiness.industryEnvironmental engineeringWater supplyGeneral MedicineComplex networkPump as Turbine (PAT)TurbineTerm (time)method of characteristicenergy savingwater distribution networkControl networkintermittent distributionbusinessEnergy (signal processing)Engineering(all)energy saving.Procedia Engineering
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Evolutionary Game Dynamics for Collective Decision Making in Structured and Unstructured Environments

2017

Abstract For a large population of players we consider a collective decision making process with three possible choices: option A or B or no option. The more popular option is more likely to be chosen by uncommitted players and cross-inhibitory signals can be sent to attract players committed to a different option. This model originates in the context of honeybees swarms, and we generalise it to accommodate other applications such as duopolistic competition and opinion dynamics. The first contribution is an evolutionary game model and a corresponding new game dynamics called expected gain pairwise comparison dynamics explaining how the strategic behaviour of the players may lead to deadlock…

Equilibrium pointNon-cooperative gamebusiness.industry020208 electrical & electronic engineeringStability (learning theory)Opinion DynamicContext (language use)02 engineering and technologyComplex networkMulti-Agent SystemsGroup decision-makingCompetition (economics)Game TheorySettore ING-INF/04 - AutomaticaControl and Systems Engineering0202 electrical engineering electronic engineering information engineeringEconomicsSocial Network020201 artificial intelligence & image processingPairwise comparisonArtificial intelligenceSettore MAT/09 - Ricerca OperativabusinessMathematical economicsIFAC-PapersOnLine
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A General Framework for Complex Network-Based Image Segmentation

2019

International audience; With the recent advances in complex networks theory, graph-based techniques for image segmentation has attracted great attention recently. In order to segment the image into meaningful connected components, this paper proposes an image segmentation general framework using complex networks based community detection algorithms. If we consider regions as communities, using community detection algorithms directly can lead to an over-segmented image. To address this problem, we start by splitting the image into small regions using an initial segmentation. The obtained regions are used for building the complex network. To produce meaningful connected components and detect …

FOS: Computer and information sciencesComputer Science - Machine LearningComputer Networks and CommunicationsComputer scienceComputer Vision and Pattern Recognition (cs.CV)Computer Science - Computer Vision and Pattern RecognitionComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMachine Learning (stat.ML)02 engineering and technologyMachine Learning (cs.LG)Statistics - Machine Learning0202 electrical engineering electronic engineering information engineeringMedia TechnologySegmentationConnected componentbusiness.industrySimilarity matrix[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringPattern recognitionImage segmentationComplex networkHardware and ArchitectureComputer Science::Computer Vision and Pattern RecognitionGraph (abstract data type)020201 artificial intelligence & image processingArtificial intelligencebusinessSoftware
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