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Fuzzy Discrete Event Simulation for Fuzzy Production Systems Analysis

IFAC Proceedings Volumes, 1998
Abstract Fuzzy production systems are characterised by vagueness in data and requirements that very often cannot be reduced to stochastic models. Therefore, such production systems cannot be analysed by using classical techniques such as Queue Theory or Discrete Simulation Analysis.
G. Perroneo, S. Noto La Diega, A. Zinno
openaire   +1 more source

Information energy of a fuzzy event and a partition of fuzzy events

IEEE Transactions on Systems, Man, and Cybernetics, 1985
In order to define a measure of the information processed by a fuzzy event and by a partition of fuzzy events, the ''information energy'' provided by a fuzzy event and partition of fuzzy events is considered. This measure integrates the statistical uncertainty resulting from the occurrence of events and the uncertainty of meaning of events that is ...
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Fuzzy subsethood and belief functions of fuzzy events

Fuzzy Sets and Systems, 2007
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Probability, Possibility and Fuzzy Events

2008
It is very common to confuse fuzzy sets theory with the theory of probabilities. Frequently membership degree is misinterpreted as probability value and the membership function as a statistic distribution function. This confusion emerges due to the fact that there is a narrow relationship among the two theories and, under certain aspects, the fuzzy ...
Eduardo Massad   +3 more
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Probability of Intuitionistic Fuzzy Events

2002
The notion of probability measure of intuitionistic fuzzy events is investigated and basic properties of that concept are examined.
Przemysław Grzegorzewski, Edyta Mrówka
openaire   +1 more source

Diagnosability of Fuzzy Discrete-Event Systems: A Fuzzy Approach

IEEE Transactions on Fuzzy Systems, 2009
In order to more effectively cope with the real-world problems of vagueness, fuzzy discrete-event systems (FDESs) were proposed by Lin and Ying recently. Then we and Cao and Ying investigated the supervisory control of FDESs independently. In this paper, we are concerned with another important issue of FDESs, the failure diagnosis.
null Fuchun Liu, null Daowen Qiu
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Event-Triggered Polynomial Fuzzy Controller for Networked Polynomial Fuzzy Systems

2018 5th IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS), 2018
This paper deals with the polynomial event-triggered control for nonlinear networked control systems (NCSs). Representing the nonlinear model using a polynomial fuzzy model, a novel polynomial event-triggered scheme is proposed which includes some existing scheme as a special case.
Guiling Li, Chen Peng
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Measure, Integrals and Fuzzy Events

2016
This chapter reviews classical measure theory including probability and Lebesgue measures. This discussion is followed by fuzzy measures, Sugeno measures, and possibilistic measures in order to understand the integration of Lebesgue, Choquet and Sugeno. These concepts are used in the development of fuzzy expected value.
Laécio Carvalho de Barros   +2 more
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A Fuzzy Discrete Event Simulator for Fuzzy Production Environment Analysis

CIRP Annals, 1998
Abstract Discrete Event Simulation is a powerful tool to help production managers in planning manufacturing systems. The necessity to rapid react to market conditions is pushing production planners to process requirements and information affected by vagueness.
G. Perrone, S. Noto La Diega, A. Zinno
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Fuzzy vs. non-fuzzy rule base for gait event detection

Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2002
A method for the detection of gait events in the electrically-stimulated walking of paraplegic subjects was developed using fuzzy system identification methods. The efficacy of various amounts of "fuzziness" (i.e., overlap of sensor measurement membership functions) of the system mas explored.
null Sau Kuen Ng, H.J. Chizeck
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