Fuzzy dynamical systems, fuzzy random fields

1995 ◽  
Vol 36 (2-3) ◽  
pp. 263-274 ◽  
Author(s):  
Sławomir Bugajski
Keyword(s):  
Dynamical Systems ◽  
Random Fields ◽  
Fuzzy Dynamical Systems ◽  
Fuzzy Random

Stability of fuzzy dynamical systems based on quasi-level-wise system

2017 ◽  
Vol 33 (6) ◽  
pp. 3515-3528 ◽  
Author(s):  
Debnarayan Khatua ◽  
Kalipada Maity
Keyword(s):  
Dynamical Systems ◽  
Fuzzy Dynamical Systems

An Efficient Numerical Simulation for Solving Dynamical Systems With Uncertainty

2017 ◽  
Vol 12 (5) ◽  
Author(s):  
Ali Ahmadian ◽  
Soheil Salahshour ◽  
Chee Seng Chan ◽  
Dumitur Baleanu
Keyword(s):  
Dynamical Systems ◽  
Stability And Convergence ◽  
Uncertain Parameters ◽  
Crucial Issue ◽  
Computational Costs ◽  
First Order ◽  
Wide Range ◽  
Linear And Nonlinear ◽  
The Stability ◽  
Fuzzy Dynamical Systems

In a wide range of real-world physical and dynamical systems, precise defining of the uncertain parameters in their mathematical models is a crucial issue. It is well known that the usage of fuzzy differential equations (FDEs) is a way to exhibit these possibilistic uncertainties. In this research, a fast and accurate type of Runge–Kutta (RK) methods is generalized that are for solving first-order fuzzy dynamical systems. An interesting feature of the structure of this technique is that the data from previous steps are exploited that reduce substantially the computational costs. The major novelty of this research is that we provide the conditions of the stability and convergence of the method in the fuzzy area, which significantly completes the previous findings in the literature. The experimental results demonstrate the robustness of our technique by solving linear and nonlinear uncertain dynamical systems.

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