TY  - GEN
AU  - Pamučar,Dragan
AU  - Marinkovic,Dragan
AU  - Kar,Samarjit
AU  - Pamučar,Dragan
AU  - Marinkovic,Dragan
AU  - Kar,Samarjit
TI  - Dynamics under Uncertainty: Modeling Simulation and Complexity
SN  - books978-3-0365-1575-5
PY  - 2021///
CY  - Basel, Switzerland
PB  - MDPI - Multidisciplinary Digital Publishing Institute
KW  - Research & information: general
KW  - bicssc
KW  - Mathematics & science
KW  - Fuzzy MARCOS
KW  - Fuzzy PIPRECIA
KW  - traffic risk
KW  - TFN
KW  - MCDM
KW  - dual-rotor
KW  - multi-frequency excitation
KW  - non-intrusive calculation
KW  - metamodel
KW  - NDSL model
KW  - AHP
KW  - criteria weights
KW  - pairwise comparisons
KW  - AES
KW  - PC
KW  - MIMO discrete-time system
KW  - state feedback and output feedback
KW  - parameter dependence
KW  - D numbers
KW  - fuzzy sets
KW  - DEMATEL
KW  - multi-criteria decision-making
KW  - multi-criteria optimization
KW  - RAFSI method
KW  - performance comparison
KW  - rank reversal
KW  - Magnetic Resonance Imaging (MRI)
KW  - wavelet transform
KW  - GARCH
KW  - LLA
KW  - LDA
KW  - KNN
KW  - BWM
KW  - BWM-I
KW  - multi-criteria
KW  - renewable energy
KW  - the CCSD method
KW  - the ITARA method
KW  - the MARCOS method
KW  - stackers
KW  - logistics
KW  - ensemble techniques
KW  - data mining
KW  - classification and discrimination
KW  - linear regression
KW  - applied mathematics general
KW  - prediction theory
KW  - theory of mathematical modeling
KW  - medical applications
KW  - empathic building
KW  - fuzzy grey cognitive maps
KW  - Thayer's emotion model
KW  - artificial emotions
KW  - affective computing
KW  - n/a
N1  - Open Access
N2  - The 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
UR  - https://mdpi.com/books/pdfview/book/4231
UR  - https://directory.doabooks.org/handle/20.500.12854/76782
ER  -