Fuzzy Evaluation Method Using Fuzzy Rule Approach in Multicriteria Analysis
Mahmod Othman, Ku Ruhana Ku-Mahamud, Azuraliza Abu Bakar (2008)
The Yugoslav Journal of Operations Research
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Mahmod Othman, Ku Ruhana Ku-Mahamud, Azuraliza Abu Bakar (2008)
The Yugoslav Journal of Operations Research
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Yaya Liu, Keyun Qin, Chang Rao, Mahamuda Alhaji Mahamadu (2017)
International Journal of Applied Mathematics and Computer Science
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The research on incomplete fuzzy soft sets is an integral part of the research on fuzzy soft sets and has been initiated recently. In this work, we first point out that an existing approach to predicting unknown data in an incomplete fuzzy soft set suffers from some limitations and then we propose an improved method. The hidden information between both objects and parameters revealed in our approach is more comprehensive. Furthermore, based on the similarity measures of fuzzy sets, a...
Przemyslaw Grzegorzewski, Olgierd Hryniewicz (1997)
Mathware and Soft Computing
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In traditional statistics all parameters of the mathematical model and possible observations should be well defined. Sometimes such assumption appears too rigid for the real-life problems, especially while dealing with linguistic data or imprecise requirements. To relax this rigidity fuzzy methods are incorporated into statistics. We review hitherto existing achievements in testing statistical hypotheses in fuzzy environment, point out their advantages or disadvantages and practical...
Dragan Z. Šaletić, Dušan M. Velašević (2000)
The Yugoslav Journal of Operations Research
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Robert K. Nowicki (2010)
International Journal of Applied Mathematics and Computer Science
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The paper presents a new approach to fuzzy classification in the case of missing data. Rough-fuzzy sets are incorporated into logical type neuro-fuzzy structures and a rough-neuro-fuzzy classifier is derived. Theorems which allow determining the structure of the rough-neuro-fuzzy classifier are given. Several experiments illustrating the performance of the roughneuro-fuzzy classifier working in the case of missing features are described.
M. R. Casals (1993)
RAIRO - Operations Research - Recherche Opérationnelle
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Adam Grabowski (2014)
Formalized Mathematics
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In this article, we continue the development of the theory of fuzzy sets [23], started with [14] with the future aim to provide the formalization of fuzzy numbers [8] in terms reflecting the current state of the Mizar Mathematical Library. Note that in order to have more usable approach in [14], we revised that article as well; some of the ideas were described in [12]. As we can actually understand fuzzy sets just as their membership functions (via the equality of membership function...
Daniel J. Fonseca, C. L. Guest, Matthew Elam, Charles L. Karr (2005)
Mathware and Soft Computing
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This paper deals with the use of fuzzy set theory as a viable alternative method for modelling and solving the stochastic assembly line balancing problem. Variability and uncertainty in the assembly line balancing problem has traditionally been modelled through the use of statistical distributions. This may not be feasible in cases where no historical data exists. Fuzzy set theory allows for the consideration of the ambiguity involved in assigning processing and cycle times and the uncertainty...
Milanka Gardašević-Filipović, Dragan Z. Šaletić (2010)
The Yugoslav Journal of Operations Research
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Miguel Delgado, José Luis Verdegay, M. Amparo Vila (1994)
Mathware and Soft Computing
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Two different definitions of a Fuzzy number may be found in the literature. Both fulfill Goguen's Fuzzification Principle but are different in nature because of their different starting points. The first one was introduced by Zadeh and has well suited arithmetic and algebraic properties. The second one, introduced by Gantner, Steinlage and Warren, is a good and formal representation of the concept from a topological point of view. The objective of this paper is...
Collan, Mikael, Fullér, Robert, Mezei, József (2009)
Journal of Applied Mathematics and Decision Sciences
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Martine De Cock, Etienne Kerre (2002)
International Journal of Applied Mathematics and Computer Science
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We present a framework of L-fuzzy modifiers for L being a complete lattice. They are used to model linguistic hedges that act on linguistic terms represented by L-fuzzy sets. In the modelling process the context is taken into account by means of L-fuzzy relations, endowing the L-fuzzy modifiers with a clear inherent semantics. To our knowledge, these L-fuzzy modifiers are the first ones proposed that are suitable to perform this representation task for a lattice L different from the...
Thien, Nguyen Van, Demetrovics, Janos, Thi, Vu Duc, Giang, Nguyen Long, Son, Nguyen Nhu (2016)
Serdica Journal of Computing
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In fuzzy granular computing, a fuzzy granular structure is the collection of fuzzy information granules and fuzzy information granularity is used to measure the granulation degree of a fuzzy granular structure. In general, the fuzzy information granularity characterizes discernibility ability among fuzzy information granules in a fuzzy granular structure. In recent years, researchers have proposed some concepts of fuzzy information granularity based on partial order relations. However,...