L. A. Zadeh, "Fuzzy logic = computing with words," IEEE Trans. Fuzzy Systems, vol. 4, pp. 103--111, 1996. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Object-Oriented Modelling with Words - Rossiter, Cao, Martin, Baldwin (Correct)
....the form of a linguistic description then a key component of this model is the representation we use for finite elements of knowledge. The field of computing with words provides us with some pointers to natural and effective knowledge descriptors using words. Zadeh proposed information granules ([14]) as a replacement for numbers in knowledge representation and reasoning. For true linguistic transparency granulisation should be invoked with respect to human perceptions. This approach, as also suggested by Zadeh ( 15] yields a vocabulary that is not only appropriately linguistic, but also ....
L.A.Zadeh, "Fuzzy Logic = Computing With Words", IEEE Transactions on Fuzzy Systems, Vol. 4, No. 2, May 1996
On Modal Decision Logics - Fan, Liau, Yao (2002) (Correct)
....formalism will play an important role in the utilization of the induced rules. A good representation formalism should have clear semantics so that a rule can be effectively validated with respect to the given data tables. In this regard, logic is one of the best choices. As indicated by Zadeh[14], human usually compute with words instead of numbers, so if we can incorporate linguistically meaningful terms into the representation formalism, then the induced rules may be more useful to the human decision makers. The rough set theory proposed by Pawlak provides an effective tool for ....
L.A. Zadeh. "Fuzzy logic = computing with words". IEEE Transactions on Fuzzy Systems, 4:103--111, 1996. 5
Discovering Human Understandable Fuzzy Diagnostic Rules - From Medical Data (2003) (Correct)
.... that fall in CI, fuzzy set theory is one of the most promising, since it can bridge the gap between the numerical world, in which often symptoms are observed and measured, and the symbolic world, in which knowledge should be expressed in order to be easy to read and understand by human users [12]. Fuzzy diagnosis is characterized by the fact that the medical diagnostic problem is often solved by a system which relies on a set of fuzzy rules [7] and hence can provide useful knowledge to physicians for the diagnosis of diseases when a set of symptoms is observed. A lot of techniques have ....
Zadeh L., "Fuzzy Logic = Computing with Words", 1996, IEEE Transactions on Fuzzy Systems, 2, pp. 103-111.
Fuzzy Adaptive Logic Networks - Witold Pedrycz Dept (Correct)
.... synergy of fuzzy sets and neural networks is multifaceted and center on the coherent treatment of data and knowledge processing: neural networks concentrate on detailed numeric processing [3,4] whereas fuzzy sets focus on granular computing thereby being positioned at the logic end of processing [2,5,13,14,17,18,19,20,21]. This point of view has resulted in a vast array of neumfuzzy systems topologies. There is also another stream of research of fuzzy neurocompufing that focuses on the synergy between (fuzzy) logic and geometry. In this combination, low end geometric constructs operate on numerical entities and ....
L.A. Zadeh, "Fuzzy logic = Computing with words", IEEE Trans Fuzzy Systems 4 103-111, 1996.
Linguistic Hedges on Trapezoidal Fuzzy Sets: A Revisit - Marín-Blázquez, Shen (Correct)
....LOWER and MID. Simulation results are provided to demonstrate the advantages of utilising the revised and newly introduced hedges for assisting fuzzy modelling, in comparison to the use of conventional ones. I. INTRODUCTION Computing with words is the fundamental con tribution of fuzzy logic [1]. Linguistic variables are variables whose values can be words rather than numbers. These words can be interpreted as se mantic labels to the fuzzy sets [2] By the use of fuzzy sets with attached semantic labels it is possible to create a human comprehensible computer representation of the ....
Lofti A. Zadeh, "Fuzzy logic = computing with words," Transactions on Fuzzy Systems, vol. 4, no. 2, pp. 102111, May 1996.
Knowledge Extraction from Neural Networks Using the.. - Kolman, Margaliot (2005) (Correct)
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L. A. Zadeh, "Fuzzy logic = computing with words," IEEE Trans. Fuzzy Systems, vol. 4, pp. 103--111, 1996.
The Fuzzy Ant - Valeri Rozin And (Correct)
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L. A. Zadeh, "Fuzzy logic = computing with words," IEEE Trans. Fuzzy Systems, vol. 4, pp. 103--111, 1996.
Nicholson's Blowflies Revisited: - Fuzzy Modeling Approach (Correct)
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L. A. Zadeh, "Fuzzy logic = computing with words," IEEE Trans. Fuzzy Systems, vol. 4, no. 2, pp. 103--111, 1996. 23
Modelling the Variation in Human Decision Making - Ozen, Garibaldi, Musikasuwan (2004) (Correct)
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L. Zadeh, "Fuzzy logic = computing with words," IEEE Transactions on Fuzzy Systems, vol. 2, pp. 103--111, 1996.
Intl. Conf. RIVF'04 - February Hanoi Vietnam (2004) (Correct)
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L.A. Zadeh, "Fuzzy Logic = Computing with Words", IEEE Transactions on Fuzzy Systems, 1996.
Choosing Membership Functions of Linguistic Terms - Garibaldi, John (2003) (Correct)
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L.A. Zadeh, "Fuzzy logic = computing with words," IEEE Transactions on Fuzzy Systems, vol. 4, no. 2, pp. 103--111, 1996.
KASER: A Qualitatively Fuzzy Object-Oriented Inference Engine - Stuart Rubin And (2002) (Correct)
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L.A. Zadeh, "Fuzzy Logic = Computing with Words," IEEE Trans. Fuzzy Syst., vol. 4, no. 2, pp. 103-111, 1996.
A Case Study to Illustrate the Use of Non-Convex.. - Garibaldi.. (2004) (Correct)
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L. Zadeh, "Fuzzy logic = computing with words," IEEE Transactions on Fuzzy Systems, vol. 4, no. 2, pp. 103--111, 1996.
Effect of Type-2 Fuzzy Membership Function Shape on Modelling .. - Ozen, Garibaldi (2004) (Correct)
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L. Zadeh, "Fuzzy logic = computing with words," IEEE Transactions on Fuzzy Systems, vol. 2, pp. 103--111, 1996.
Modelling the Variation in Human Decision Making - Ozen, Garibaldi, Musikasuwan (2004) (Correct)
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L. Zadeh, "Fuzzy logic = computing with words," IEEE Transactions on Fuzzy Systems, vol. 2, pp. 103--111, 1996.
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