Basic concepts and history of fuzzy set theory and fuzzy logic

Klir, George J.; Yuan, Bo

doi:10.1887/0750304278/b438c1

Cited by 73 publications

(113 citation statements)

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“…(34) are based on so-called triangular norms, t-norms and t-conorms (or s-norms). As many operators exist, we refer to the literature (Klir & Yuan, 1995). The union and intersection can be interpreted as aggregation operations.…”

Section: Fuzzy Set Theorymentioning

confidence: 99%

“…The aggregation operator h is a bounded, monotonic, increasing, symmetric, and idempotent operator (Klir & Yuan, 1995). Beside the fuzzy union and intersection, which can be defined in different ways, the so called averaging operators play an important role in aggregation.…”

Section: Fuzzy Set Theorymentioning

confidence: 99%

“…The construction of membership function can be established by different concepts; e. g. cf. (Bocklisch & Priber, 1986), (Klir & Yuan, 1995), (Bossé et al, 2007), (Lohweg & Mönks, 2010a).…”

Section: Fuzzy Set Theorymentioning

confidence: 99%

“…Let α i be a certain value of μ x (A α i | θ), then A α i denotes it corresponding α-cut. The associated possibility function is then defined by (Klir & Yuan, 1995):…”

Section: Possibility Theorymentioning

confidence: 99%

See 3 more Smart Citations

A Possibilistic Framework for Sensor Fusion with Monitoring of Sensor Reliability

Lohweg¹,

Voth²,

Glock³

2011

Sensor Fusion - Foundation and Applications

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Section: Fuzzy Set Theorymentioning

confidence: 99%

Section: Fuzzy Set Theorymentioning

confidence: 99%

Section: Fuzzy Set Theorymentioning

confidence: 99%

“…Let α i be a certain value of μ x (A α i | θ), then A α i denotes it corresponding α-cut. The associated possibility function is then defined by (Klir & Yuan, 1995):…”

Section: Possibility Theorymentioning

confidence: 99%

See 2 more Smart Citations

A Possibilistic Framework for Sensor Fusion with Monitoring of Sensor Reliability

Lohweg¹,

Voth²,

Glock³

2011

Sensor Fusion - Foundation and Applications

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“…Nevertheless, according the law of nature, information regarding the physical phenomena involved are often represented not by true values, but instead the values are represented by uncertainty. Klir et al [1] defines the concept of fuzzy numbers which exist form many phenomena that cannot be measured with precise values.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy version of a developed fourth order Runge Kutta method for solving differential equations with fuzzy initial values

Ramli

Din²,

Salleh³

2016

AIP Conference Proceedings

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Abstract. In this paper, numerical algorithm is applied for solving fuzzy differential equations based on generalized Hukuhara differentiability. In order to enhance the order of accuracy of the solutions, a developed fourth order Runge-Kutta method is apply for solving fuzzy differential equations. The purpose of this study is to explore the explicit methods which we believe that most of the explicit methods can be improved and modified to cater and solve fuzzy differential equations. This paper is divided into six sections. In the first section, some basic definitions and theorem are reviewed. The numerical examples are given to illustrate the efficiency of the method and the comparison with the existing method is discussed.

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Multiple criteria and fuzzy based evaluation of logistics performance for intermodal transportation

Hanaoka

Kunadhamraks

2009

J of Advced Transportation

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This paper presents a framework to evaluate the logistics performance of intermodal freight transportation. Fuzzy set techniques are applied to assess the logistics performance within the decision process of freight operators. Using a fuzzy-based approach, fuzzy-AHP is applied to assess the criteria by different judgment procedures. Consequently, fuzzy-MCDM is used to assess operators' perception of the logistics performance via proper assignment of numerical scores. The subjective judgments for hierarchical criteria are transformed into fuzzy degrees of score. The methodology provides an alternative approach to facilitate the importance of a set of performance criteria. It can also entail use of improved corresponding parameters to develop a better freight transport system.

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Basic concepts and history of fuzzy set theory and fuzzy logic

Cited by 73 publications

References 0 publications

A Possibilistic Framework for Sensor Fusion with Monitoring of Sensor Reliability

A Possibilistic Framework for Sensor Fusion with Monitoring of Sensor Reliability

Fuzzy version of a developed fourth order Runge Kutta method for solving differential equations with fuzzy initial values

Multiple criteria and fuzzy based evaluation of logistics performance for intermodal transportation

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