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Dynamics under Uncertainty: Modeling Simulation and Complexity

dc.contributor.editorPamučar, Dragan
dc.contributor.editorMarinkovic, Dragan
dc.contributor.editorKar, Samarjit
dc.date.accessioned2022-01-11T13:42:06Z
dc.date.available2022-01-11T13:42:06Z
dc.date.issued2021
dc.identifierONIX_20220111_9783036515762_517
dc.identifier.urihttps://directory.doabooks.org/handle/20.500.12854/76782
dc.description.abstractThe dynamics of systems have proven to be very powerful tools in understanding the behavior of different natural phenomena throughout the last two centuries. However, the attributes of natural systems are observed to deviate from their classical states due to the effect of different types of uncertainties. Actually, randomness and impreciseness are the two major sources of uncertainties in natural systems. Randomness is modeled by different stochastic processes and impreciseness could be modeled by fuzzy sets, rough sets, Dempster–Shafer theory, etc.
dc.languageEnglish
dc.subject.classificationthema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: generalen_US
dc.subject.classificationthema EDItEUR::P Mathematics and Scienceen_US
dc.subject.otherFuzzy MARCOS
dc.subject.otherFuzzy PIPRECIA
dc.subject.othertraffic risk
dc.subject.otherTFN
dc.subject.otherMCDM
dc.subject.otherdual-rotor
dc.subject.othermulti-frequency excitation
dc.subject.othernon-intrusive calculation
dc.subject.othermetamodel
dc.subject.otherNDSL model
dc.subject.otherAHP
dc.subject.othercriteria weights
dc.subject.otherpairwise comparisons
dc.subject.otherAES
dc.subject.otherPC
dc.subject.otherMIMO discrete-time system
dc.subject.otherstate feedback and output feedback
dc.subject.otherparameter dependence
dc.subject.otherD numbers
dc.subject.otherfuzzy sets
dc.subject.otherDEMATEL
dc.subject.othermulti-criteria decision-making
dc.subject.othermulti-criteria optimization
dc.subject.otherRAFSI method
dc.subject.otherperformance comparison
dc.subject.otherrank reversal
dc.subject.otherMagnetic Resonance Imaging (MRI)
dc.subject.otherwavelet transform
dc.subject.otherGARCH
dc.subject.otherLLA
dc.subject.otherLDA
dc.subject.otherKNN
dc.subject.otherBWM
dc.subject.otherBWM-I
dc.subject.othermulti-criteria
dc.subject.otherrenewable energy
dc.subject.otherthe CCSD method
dc.subject.otherthe ITARA method
dc.subject.otherthe MARCOS method
dc.subject.otherstackers
dc.subject.otherlogistics
dc.subject.otherensemble techniques
dc.subject.otherdata mining
dc.subject.otherclassification and discrimination
dc.subject.otherlinear regression
dc.subject.otherapplied mathematics general
dc.subject.otherprediction theory
dc.subject.othertheory of mathematical modeling
dc.subject.othermedical applications
dc.subject.otherempathic building
dc.subject.otherfuzzy grey cognitive maps
dc.subject.otherThayer’s emotion model
dc.subject.otherartificial emotions
dc.subject.otheraffective computing
dc.subject.othern/a
dc.titleDynamics under Uncertainty: Modeling Simulation and Complexity
dc.typebook
oapen.identifier.doi10.3390/books978-3-0365-1575-5
oapen.relation.isPublishedBy46cabcaa-dd94-4bfe-87b4-55023c1b36d0
oapen.relation.isbn9783036515762
oapen.relation.isbn9783036515755
oapen.pages210
oapen.place.publicationBasel, Switzerland


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