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Investigation on visualization, analysis, and control of complex networks dynamics

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dc.title Investigation on visualization, analysis, and control of complex networks dynamics en
dc.contributor.author Zelinka, Ivan
dc.contributor.author Davendra, Donald
dc.contributor.author Jašek, Roman
dc.contributor.author Šenkeřík, Roman
dc.relation.ispartof International Journal of Disaster Recovery and Business Continuity
dc.identifier.issn 2160-9500 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2012
utb.relation.volume 1
utb.relation.issue 3
dc.citation.spage 48
dc.citation.epage 73
dc.type article
dc.language.iso en
dc.publisher IGI Global
dc.identifier.doi 10.4018/ijeoe.2012070103
dc.relation.uri https://www.igi-global.com/gateway/article/68417
dc.subject chaos en
dc.subject complex networks en
dc.subject control of complex systems en
dc.subject coupled map lattices en
dc.subject network dynamics en
dc.subject visualization en
dc.description.abstract In this article the authors discuss a new method of the so-called complex networks dynamics and its visualization by means of so called coupled map lattices method. The main aim of this article is to investigate whether it is possible to visualize complex network dynamics by means of the same method that is used to model spatiotemporal chaos. The authors suggest using coupled map lattices system to simulate complex network so that each site is equal to one vertex of complex network. Interaction between network vertices is in coupled map lattices equal to the strength of mutual influence between system sites. To promote their ideas, two kinds of complex networks dynamics has been selected for visualization, i.e., network with increasing number of vertices and network with constant number of vertices. All results have been properly visualized and explained. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1010710
utb.identifier.obdid 43869198
utb.identifier.wok 000218770300002
utb.source J-wok
dc.date.accessioned 2021-12-17T14:35:12Z
dc.date.available 2021-12-17T14:35:12Z
dc.description.sponsorship Ministry of Education of the Czech RepublicMinistry of Education, Youth & Sports - Czech Republic [MSM 7088352101]; Grant Agency of the Czech RepublicGrant Agency of the Czech Republic [GACR 102/09/1680]; framework of the IT4Innovations Centre of Excellence project [CZ.1.05/1.1.00/02.0070]; Operational Programme 'Research and Development for Innovations' - Structural Funds of the European Union; state budget of the Czech Republic
utb.ou CEBIA-Tech
utb.contributor.internalauthor Jašek, Roman
utb.contributor.internalauthor Šenkeřík, Roman
utb.fulltext.affiliation Ivan Zelinka (Technical University of Ostrava, Czech Republic), Donald Davendra (Technical University of Ostrava, Czech Republic), Roman Jašek (Tomas Bata University in Zlin, Czech Republic) and Roman Šenkerík (Tomas Bata University in Zlin, Czech Republic)
utb.fulltext.dates -
utb.fulltext.references Boccaletti S. Latora V. Moreno Y. Chavez M. Hwang D.-U. (2006). Complex networks: Structure and dynamics.Physics Reports, 424(4-5), 175–308. 10.1016/j.physrep.2005.10.009 Chen G. (2000). Controlling chaos and bifurcations in engineering systems. Boca Raton, FL: CRC Press. Chen G. Dong X. (1998). From chaos to order: Methodologies, perspectives and applications. Singapore: World Scientific. Dashora Y. Kumar S. Shukla N. Tiwari M. K. (2007). Improved and generalized learning strategies for dynamically fast and statistically robust evolutionary algorithms.Engineering Applications of Artificial Intelligence, 21(4), 525–547. 10.1016/j.engappai.2007.06.005 Deilami M. Rahmani C. Motlagh M. (2007). Control of spatio-temporal on-off intermittency in random driving diffusively coupled map lattices.Chaos, Solitons, and Fractals, 41(1), 113–122. 10.1016/j.chaos.2007.11.016 Dorogovtsev S. N. Mendes J. F. F. (2002). Evolution of networks.Advances in Physics, 51, 1079. 10.1080/00018730110112519 Fogel D. B. (1998). Unearthing a fossil from the history of evolutionary computation.Fundamenta Informaticae, 35(1-4), 1–16. Gilmore R. Lefranc M. (2002). The topology of chaos: Alice in stretch and squeezeland. New York, NY: Wiley-Interscience. Gopal E. V. Munaga V. N. K. Prasad V. R. (2010). Fast and accurate watermark retrieval using evolutionary algorithms.International Journal of Computer Information Systems and Industrial Management Applications, 2, 121–136. Grebogi C. Lai Y. C. (1999). Controlling chaos. In SchusterH. (Ed.), Handbook of chaos control. New York, NY: Wiley-Interscience. He Q. Wang L. (2007). An effective co-evolutionary particle swarm optimization for constrained engineering design problems.Engineering Applications of Artificial Intelligence, 20(1), 89–99. 10.1016/j.engappai.2006.03.003 Hilborn R. (1994). Chaos and nonlinear dynamics. Oxford, UK: Oxford University Press. Holland J. (1975). Adaptation in natural and artificial systems. Ann Arbor, MI: University of Michigan Press. Jeyakumar G. Velayutham C. S. (2010). An empirical performance analysis of differential evolution variants on unconstrained global optimization problems.International Journal of Computer Information Systems and Industrial Management Applications, 2, 77–86. Just W. (1999). Principles of time delayed feedback control. In SchusterH. (Ed.), Handbook of chaos control. New York, NY: Wiley-Interscience. Just W. Benner H. Reibold E. (2003). Theoretical and experimental aspects of chaos control by time-delayed feedback.Chaos (Woodbury, N.Y.), 13, 259–266. 10.1063/1.149695512675432 Li L. Wenxin L. David A. C. (2007). Particle swarm optimization-based parameter identification applied to permanent magnet synchronous motors.Engineering Applications of Artificial Intelligence, 21(7), 1092–1100. 10.1016/j.engappai.2007.10.002 Lorenz E. (1963). Deterministic nonperiodic flow.Journal of the Atmospheric Sciences, 20(2), 130–140. 10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2 May R. (1976). Simple mathematical model with very complicated dynamics.Nature, 261, 45–67. 10.1038/261459a0 Meyn S. (2007). Control techniques for complex networks. Cambridge, UK: Cambridge University Press. 10.1017/CBO9780511804410 Ott E. Grebogi C. Yorke J. (1990). Controlling chaos.Physical Review Letters, 64, 1196–1199. 10.1103/PhysRevLett.64.119610041332 Rechenberg I. (1973). Evolutionsstrategie - Optimierung technischer Systeme nach Prinzipien der biologischen Evolution. Stuttgart, Germany: Frommann-Holzboog. Richter, H. (2002). An evolutionary algorithm for controlling chaos: The use of multi-objective fitness functions. In J. J. M. Guervos, P. A. Adamidis, H. G. Beyer, H. P. Schwefel, & J.-L. Fernández-Villacañas (Eds.), Proceedings of the 7th International Conference on Parallel Problem Solving from Nature (LNCS, 2439, pp. 308-317). Richter, H. (2005, September 2-5). A study of dynamic severity in chaotic fitness landscapes. In Proceedings of the IEEE Congress on Evolutionary Computation (Vol. 3, pp. 2824-2831). Richter, H. (2006). Evolutionary optimization in spatio-temporal fitness landscapes. In T. P. Runarsson, H.-G. Beyer, E. Burke, J. J. Merelo-Guervós, L. D. Whitley, & X. Yao (Eds.), Proceedings of the 9th International Conference on Parallel Problem Solving from Nature (LNCS 4193, pp. 1-10). Richter H. Reinschke K. (2000). Optimization of local control of chaos by an evolutionary algorithm.Physica D. Nonlinear Phenomena, 144, 309–334. 10.1016/S0167-2789(00)00080-4 Schuster H. (1999). Handbook of chaos control. New York, NY: Wiley-Interscience. 10.1002/3527607455 Schwefel H. (1974). Numerische Optimierung von Computer-Modellen.Journal of Applied Mathematics and Mechanics, 60(5), 272. Senkerik, R., Zelinka, I., & Navratil, E. (2006). Optimization of feedback control of chaos by evolutionary algorithms. In Proceedings of the 1st IFAC Conference on Analysis and Control of Chaotic Systems, Reims, France. Stewart I. (2000). TheLorenzattractorexists.Nature, 406, 948–949. 10.1038/3502320610984036 Turing A. (1969). Intelligent machinery.Machine Intelligence, 5, 3–23. Wang X. Chen G. (2008). Chaotification via arbitrarily small feedback controls: Theory, method, and applications.International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, 10, 549–570. Zelinka, I. (2006). Investigation on real-time deterministic chaos control by means of evolutionary algorithms. In Proceedings of the 1st IFAC Conference on Analysis and Control of Chaotic Systems, Reims, France (Vol. 1, pp. 211-217). Zelinka I. (2008). Real-time deterministic chaos control by means of selected evolutionary algorithms.Engineering Applications of Artificial Intelligence, 22(2), 283–297. 10.1016/j.engappai.2008.07.008 Zelinka I. Chen G. Celikovsky S. (2008). Chaos synthesis by means of evolutionary algorithms.International Journal of Bifurcation and Chaos in Applied Sciences and Engineering, 18(4), 911–942. 10.1142/S021812740802077X Zelinka I. Davendra D. (in press). Investigation on relations between complex networks and evolutionary algorithm dynamics.International Journal of Computer Information Systems and Industrial Management Applications. Zou Y. Luo X. Chen G. (2006). Pole placement method of controlling chaos in DC-DC buck converters.Chinese Physics, 15, 1719–1724. 10.1088/1009-1963/15/8/015
utb.wos.affiliation [Zelinka, Ivan; Davendra, Donald] Tech Univ Ostrava, Ostrava, Czech Republic; [Jasek, Roman; Senkerik, Roman] Tomas Bata Univ, Zlin, Czech Republic
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