Results 251 to 260 of about 17,671,836 (283)

Fuzzy stopping in continuous-time dynamic fuzzy systems

Fuzzy Sets and Systems, 2002
The paper discusses a stopping problem in continuous-time dynamic fuzzy system, using fuzzy stopping times, under some different estimation of fuzzy rewards. The paper develops fuzzy stopping times in a continuous time fuzzy system. Also the paper presents the optimality equations for the optimal fuzzy rewards in terms of variational inequalities.
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Dynamic Neural Fuzzy Inference System

2009
This paper proposes an extension to the original offline version of DENFIS. The new algorithm, DyNFIS, replaces original triangular membership function with Gaussian membership function and use back-propagation to further optimizes the model. Fuzzy rules are created for each clustering centre based on the clustering outcome of evolving clustering ...
Yuan-Chun Hwang, Qun Song 0002
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Fuzzy Dynamic Programming with Stochastic Systems

1988
Multistage 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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Qualitative-fuzzy system identification of complex dynamical systems

2007 IEEE International Fuzzy Systems Conference, 2007
Fuzzy 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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Sliding Mode Control of Fuzzy Dynamic Systems

2006 9th International Conference on Control, Automation, Robotics and Vision, 2006
In this paper, a sliding mode control scheme is developed for a class of complex nonlinear systems with their T-S fuzzy models. It is shown that a set of extreme fuzzy subsystems are first derived, and a constructive sliding mode control law is then developed to guarantee the stability of the closed-loop fuzzy system.
Suiyang Khoo, Zhihong Man, Shengkui Zhao
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"Evolution of fuzzy systems and dynamics theory"

2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291), 2003
There are a few equations in theoretical physics, which in a slightly different modification cover dynamic problems of most physical systems. Moreover, in a mystical way, the same types of equations appear in completely "non-physical" areas like finance (Black-Scholes equation), political science (voting theory), ecology (population dynamics), etc.
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Dynamic Fuzzy Clustering for Recommender Systems

2005
Collaborative filtering is the most successful recommendation technique. In this paper, we apply the concept of time to collaborative filtering algorithm. We propose dynamic fuzzy clustering algorithm and apply it to collaborative filtering algorithm for dynamic recommendations.
Sung-Hwan Min, Ingoo Han
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On the observability of fuzzy dynamical control systems (I)

Fuzzy Sets and Systems, 2000
The authors study a fuzzy logic system from the aspect of fuzzy differential equations. One of its features, observability, will be studied. Given the input and output, one can detect the initial state limited to some range. A new concept called ``likelihood'', will be used to indicate on which level and along which solution the state is most likely ...
Zouhua Ding, Ming Ma 0001, Abraham Kandel   +2 more
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On the observability of fuzzy dynamical control systems (II)

Fuzzy Sets and Systems, 2000
[For Part I see ibid. 111, No. 2, 225-236 (2000; Zbl 0976.93051).] Deterministic control systems with fuzzy inputs are used to generate a fuzzy dynamic control system (FDCS). Sufficient conditions are given then for the observability of a FDCS: Given the input-output rule bases, the rule base for the initial state can be determined. An example is given.
Zouhua Ding, Abraham Kandel
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Fuzzy System Dynamics of Manpower Systems

2014
Manpower recruitment and training in uncertain and turbulent environments is a challenge to decision makers in large organizations. In the absence of numerical precision on market growth and the ensuing manpower demand, designing manpower planning policies is vital. Often times, companies incur losses due to overstaffing and/or understaffing.
Michael Mutingi, Charles Mbohwa
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