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Conditional fuzzy entropy of fuzzy dynamical systems
Fuzzy Sets and Systems, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yan, Kesong, Zeng, Fanping
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Sliding Mode Control of Markovian Jump Fuzzy Systems: A Dynamic Event-Triggered Method
IEEE transactions on fuzzy systems, 2021In this article, the sliding mode control (SMC) problem is addressed for a class of Markovian jump systems via the T–S fuzzy model. First, in order to reduce the frequency of state transmission for alleviating congestion phenomenon in the bandwidth ...
Z. Cao, Y. Niu, H. Lam, Jiancong Zhao
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Fuzzy dynamical systems, fuzzy random fields
Reports on Mathematical Physics, 1995zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Fuzzy stopping of a dynamic fuzzy system
1998 Second International Conference. Knowledge-Based Intelligent Electronic Systems. Proceedings KES'98 (Cat. No.98EX111), 2002This paper discusses an optimal stopping problem of fuzzy systems with fuzzy rewards in a class of fuzzy stopping times, which are extended from usual stopping times. Some properties regarding the optimal fuzzy stopping times are presented.
M. Kurano +3 more
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Data-Knowledge-Based Fuzzy Neural Network for Nonlinear System Identification
IEEE transactions on fuzzy systems, 2020Many nonlinear dynamical systems are usually lack of abundant datasets since the data acquiring process is time consuming. It is difficult to utilize the incomplete datasets to build an effective data-driven model to improve the industry productivity. To
Xiaolong Wu +3 more
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Qualitative-fuzzy system identification of complex dynamical systems
2007 IEEE International Fuzzy Systems Conference, 2007Fuzzy systems have been proved to be excellent candidates for system dynamics identification. However, they are affected by two drawbacks: the resulting nonlinear model (i) does not guarantee that the generalization property holds unless a large amount of samples is employed, and (ii) is not understandable from a physical viewpoint. These drawbacks are
Guglielmann R, Ironi L
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Fuzzy Dynamic Programming with Stochastic Systems
1988Multistage decision making in a fuzzy environment (fuzzy constraints, fuzzy goals and fuzzy decisions) is considered. As a tool for solving these problems, fuzzy dynamic programming for the case of a deterministic and fuzzy system under control is provided. Then, the case of a stochastic system under control is discussed in detail. Two formulations are
Fedrizzi, Mario, A. Esogbue, J. Kacprzyk
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1994
The aim of this paper is to study fuzzy dynamic systems. The role of fuzzy sets in formation of a conceptual and computational platform for symbolic and numerical information processing is identified. We summarize essential properties of fuzzy partitions developed with the aid of families of fuzzy sets.
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The aim of this paper is to study fuzzy dynamic systems. The role of fuzzy sets in formation of a conceptual and computational platform for symbolic and numerical information processing is identified. We summarize essential properties of fuzzy partitions developed with the aid of families of fuzzy sets.
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Generators of fuzzy dynamical systems
Fuzzy Sets and Systems, 2000This work is devoted to the ergodic properties of fuzzy dynamical systems. To this end the authors introduce the generators of fuzzy dynamical system and present a fuzzy version of the Kolmogorov-Sinai theorem concerning the entropy of a fuzzy dynamical system. This theorem allows them to compute the entropy for a class of fuzzy systems. Moreover, they
Dumitrescu, D. +2 more
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Fuzzy modelling of dynamic systems
Proceedings of 26th Southeastern Symposium on System Theory, 2002This paper deals with fuzzy modeling of complex dynamic systems. Fuzzy relational equations are used to describe dynamic systems' behavior. A prediction algorithm is proposed and the procedure to update the fuzzy relation of the model as new measurements are collected is discussed. The algorithm is applied to the prediction of chaotic time-series. >
M.B. Ghalia, A.T. Alouani
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