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Dynamics under Uncertainty: Modeling Simulation and Complexity

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 uncerta...

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Bibliographic Details
Main Author: Pamučar, Dragan
Other Authors: Marinkovic, Dragan, Kar, Samarjit
Format: eBook
Language:English
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
Subjects:
Multi-frequency Excitation
Performance Comparison
Data Mining
Artificial Emotions
Garch
Bwm
Tfn
Wavelet Transform
Renewable Energy
Fuzzy Grey Cognitive Maps
Mathematics & Science / Bicssc
Empathic Building
N/a
Mcdm
Ahp
Pc
Multi-criteria Optimization
Linear Regression
Thayer's Emotion Model
Rafsi Method
Lda
Stackers
Ensemble Techniques
Criteria Weights
Fuzzy Piprecia
Dual-rotor
Fuzzy Sets
Mimo Discrete-time System
Fuzzy Marcos
Metamodel
Applied Mathematics General
Research & Information: General / Bicssc
Logistics
Rank Reversal
Ndsl Model
Theory Of Mathematical Modeling
Aes
Pairwise Comparisons
The Itara Method
Dematel
Multi-criteria Decision-making
Magnetic Resonance Imaging (mri)
Non-intrusive Calculation
Medical Applications
The Ccsd Method
Bwm-i
Multi-criteria
Prediction Theory
Traffic Risk
Affective Computing
D Numbers
Parameter Dependence
The Marcos Method
Lla
State Feedback And Output Feedback
Classification And Discrimination
Knn
Online Access:
Collection: Directory of Open Access Books - Collection details see MPG.ReNa
Description
Summary: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.
Item Description:Creative Commons (cc), https://creativecommons.org/licenses/by/4.0/
Physical Description:1 electronic resource (210 p.)
ISBN:9783036515755
books978-3-0365-1575-5
9783036515762

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