Distance and similarity measures for fuzzy operators

Balopoulos, Victor; Hatzimichailidis, Anestis G.; Papadopoulos, Basil K.

doi:10.1016/j.ins.2007.01.005

Cited by 58 publications

(45 citation statements)

References 13 publications

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“…In this procedure, to start the process, we assume each data point has its own cluster, and with each step of the clustering process, these clusters are combined to form larger clusters, in an iterative way. "Similarity" among each cluster's members is measured through an Euclidian distance formula (see [18]). …”

Section: Fig 2 Scenario Tree Generation/reductionmentioning

confidence: 99%

Uncertainty in Partner Selection for Virtual Enterprises

Crispim

Sousa

2009

Leveraging Knowledge for Innovation in Collaborative Networks

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Abstract.A virtual enterprise (VE) is a temporary organization that pools the core competencies of its member enterprises and exploits fast changing market opportunities. The success of such an organization is strongly dependent on its composition, and the selection of partners becomes therefore a crucial issue. This problem is particularly difficult because of the uncertainties related to information, market dynamics, customer expectations and technology speed up. In this paper we propose an integrated approach to rank alternative VE configurations in business environments with uncertainty, using an extension of the TOPSIS method for fuzzy data, improved through the use of a stochastic multiobjective tabu search meta-heuristic. Preliminary computational results clearly demonstrate the potential of this approach for practical application.

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Section: Fig 2 Scenario Tree Generation/reductionmentioning

confidence: 99%

Uncertainty in Partner Selection for Virtual Enterprises

Crispim

Sousa

2009

Leveraging Knowledge for Innovation in Collaborative Networks

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“…In [6], Biswas defined and studied fuzzy inner product spaces in linear space. Since then some mathematicians have defined fuzzy metrics and norms on a linear space from various points of view [5,20,30,45,48]. In 1994, Cheng and Mordeson introduced a definition of fuzzy norm on a linear space in such a manner that the corresponding induced fuzzy metric is of Kramosil and Michalek type [29].…”

Section: Introductionmentioning

confidence: 99%

Hyers-Ulam stability of derivations in fuzzy Banach space

Lü¹,

Xie²,

Liu³

et al. 2016

J. Nonlinear Sci. Appl.

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“…In [6], Biswas defined and studied fuzzy inner products on linear spaces. Since then some mathematicians have defined fuzzy metrics and norms on linear spaces from various points of view [4,8,16,31,33]. In 1994, Cheng and Mordeson introduced a definition of fuzzy norms on linear spaces in such a manner that the corresponding induced fuzzy metrics are of Kramosil and Michalek type.…”

Section: Introductionmentioning

confidence: 99%

Stability of a Quadratic Functional Equation in Intuitionistic Fuzzy Normed Spaces

Bae¹,

Park²

2011

Communications of the Korean Mathematical Society

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Abstract. In this paper, we determine some stability results concerning the 2-dimensional vector variable quadratic functional equation f (x + y, z + w) + f (x − y, z − w) = 2f (x, z) + 2f (y, w) in intuitionistic fuzzy normed spaces (IFNS). We define the intuitionistic fuzzy continuity of the 2-dimensional vector variable quadratic mappings and prove that the existence of a solution for any approximately 2-dimensional vector variable quadratic mapping implies the completeness of IFNS.

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Distance and similarity measures for fuzzy operators

Cited by 58 publications

References 13 publications

Uncertainty in Partner Selection for Virtual Enterprises

Uncertainty in Partner Selection for Virtual Enterprises

Hyers-Ulam stability of derivations in fuzzy Banach space

Stability of a Quadratic Functional Equation in Intuitionistic Fuzzy Normed Spaces

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