fuzzy systems
Top PDF fuzzy systems:
A view on Fuzzy Systems for big data: progress and opportunities
... Mining systems towards a new functional paradigm that allows at working with Big ...on fuzzy systems stand out for many ...of systems, their migration to the Big Data environment in the ...
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Fuzzy systems: case study classification of fruit Mc Stipitata Vaug (Áraza)
... The overall objective of the research was to extract the human expert knowledge and be able to implement it in a programming block that made the human task with the lowest possible error. In this article the objective ...
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A Comparison of Fuzzy Clustering Algorithms Applied to Feature Extraction on Vineyard
... 1. R. Babuka, P.J. van der Veen, and U. Kaymak. Improved covariance estimation for gustafson-kessel clustering. In Fuzzy Systems, 2002. FUZZ-IEEE’02. Proceedings of the 2002 IEEE International Conference ...
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A review of artificial intelligent approaches applied to part accuracy prediction
... and fuzzy systems have been recently applied for surface roughness ...n-rule fuzzy models by a parametric search on the experimental data. The fuzzy model with the least number of rules with ...
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Automatic lateral control for unmanned vehicles via genetic algorithms
... McCormick, Simultaneous design of membership functions and rule sets for fuzzy controller using genetic algorithms, IEEE Transactions on Fuzzy Systems 3 (2) (1995) 129-139. Barro, Desi[r] ...
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Evolution of recurrent fuzzy controllers
... genetic fuzzy systems [2], the incorporation of previous knowledge (knowledge insertion) consists in the definition of fuzzy sets for the input variables and fuzzy ...for fuzzy ...
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Fuzzy strict preference relations compatible with fuzzy orderings
... of fuzzy preference modelling is the con- struction of a fuzzy strict preference relation and a fuzzy indifference relation from a fuzzy weak preference ...of fuzzy weak prefer- ence ...
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Ranking Alternatives on the Basis of the Intensity of Dominance and Fuzzy Logic within MAUT
... scribed by fuzzy numbers. The method is based on the distance of a fuzzy number. to a constant, where the generalization of the left and right fuzzy numbers, GLRFN,[r] ...
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Fuzzy Iron
... Se propone sustituir el control mecánico de las planchas por un control electrónico basado en lógica difusa, que mantenga dentro de un rango más estable la temperatura y que tome en cuen[r] ...
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Hybrid Self-Learning Fuzzy PD + I Control of Unknown SISO Linear and Nonlinear Systems
... At the beginning when artificial intelligence field begun, the design of intelligent controllers based their solutions on actual human behavior [2] and many techniques were developed to handle this situation like neural ...
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Robust Fuzzy Clustering via Trimming and Constraints
... Trimming has a long history as a simple way to provide robustness to statistical procedures. Its application in clustering needs to be done by taking into account the possibility of discarding “bridge points”. A sensible ...
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Hybrid Self Learning Fuzzy PD + I Control of Unknown SISO Linear and Nonlinear Systems
... Other rule-based control approaches use non-fuzzy rules, that is, expert systems. However, those expert systems are used normally at supervisory level or are ad-hoc to specific problems. An expert ...
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Diseño simplificado de controladores fuzzy MIMO con estructuras fuzzy SISO
... controlador fuzzy MIMO puede ser complicado por las implicancias que tiene relacionar todas las variables de entrada y de salida ...controlador fuzzy SISO propuesto resulta bastante simple y requiere un ...
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Closed form estimates of the domain of attraction for nonlinear systems via fuzzy polynomial models
... Abstract—In this work, the domain of attraction of the origin of a nonlinear system is estimated in closed-form via level sets with polynomial boundary, iteratively computed. In particular, the domain of attraction is ...
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On the notion of fuzzy adjunctions between fuzzy orders
... On underlying fuzzy framework is that of the L -fuzzy sets, where L = (L, ∨, ∧, ⊤, ⊥, ⊗, →) is a residuated lattice. A L -fuzzy set X is a mapping from the universe set, say A, to the lattice L, i.e. ...
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Tuning Up Fuzzy inference systems by using optimization algorithms for the classification of solar flares
... of fuzzy rules, a data base that defines the membership functions of the fuzzy sets used in fuzzy rules, the fuzzy inference engine, the fuzzifier and defuzzifier ...a fuzzy basis ...
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TítuloRule base reduction on a self learning fuzzy controller
... Training a fuzzy rule base requires a pattern algorithm to be learned by a fuzzy rule base. Such a pattern algorithm is used as trainer on the rule base. The trainer is a virtual control algorithm, which ...
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TítuloDesarrollo y optimización de metodologías para el diseño e implementación de sistemas electrohidráulicos y electroneumáticos eficientes
... 2007, "The design of the hydraulic model tests control system based on fuzzy self-adaptive PID algorithm", Proceedings of the International Conference on Intelligent Systems and Knowledg[r] ...
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Algorithms for learning fuzzy linguistic rule-based systems in high-dimensional problems
... The fuzzy variables have been modeled through triangular symmetrical fuzzy partitions, considering 7 labels for each linguistic variable. We have fixed the minimum support as 5% of the instances of the ...
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Searching for a consensus similarity function for generalized trapezoidal fuzzy numbers
... Chen, A new approach for fuzzy risk analysis based on similarity measures of generalized fuzzy numbers, Expert Systems with Ap. plications, 36, 589-598, (2009)[r] ...
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