On the simultaneous associativity ofF(x, y) andx+y−F(x, y)

Frank, Michael

doi:10.1007/bf02189866

Cited by 942 publications

(312 citation statements)

References 8 publications

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“…However, one potential drawback of the aforementioned operators is that the results are sensitive to the value of an operator-related parameter, and a minor change in the value of this parameter could reflect significant variations in the final decision. Similar concerns are associated with various other well-known operators such as Dombi's operator [5,6], Hamacher's operator [7], Frank's operator [8], Weber's operators [9], Dubois and Prade's operator [10], and Schweizer's operator [11], among many others. However, one operator, namely the Einstein operator, does not suffer from the drawback, since there is no operatorrelated parameter associated with that.…”

Section: Introductionmentioning

confidence: 76%

Application of Fuzzy Einstein Operator to Multi-Criteria Decision-Making for Selection of Wind Turbine Type with Nominal Power of 2000 K

Khan¹

2016

IJCNT

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Abstract:Wind energy has emerged as a potential alternative to traditional sources of fuel. One key factor that contributes to efficient harnessing of wind energy from a wind farm is the type of turbines used in that farm. However, selection of a specific wind turbine type is not a simple task due to several decision criteria, such as turbine's power rating, and height of tower on which a turbine is mounted, among others. This selection process is further complicated by the presence of conflicts between the decision criteria. Therefore, a decision is desired that provides the best balance between all selection criteria. Considering the complexities involved in the decision-making process, this paper presents a fuzzy logic based decision-making approach for selection of the most appropriate wind turbine for a specific wind farm using fuzzy Einstein operator. The proposed approach is applied to data collected from a potential site. Results indicate that the proposed approach was effective in finding the optimal turbine from a set of available turbines.

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Section: Introductionmentioning

confidence: 76%

Application of Fuzzy Einstein Operator to Multi-Criteria Decision-Making for Selection of Wind Turbine Type with Nominal Power of 2000 K

Khan¹

2016

IJCNT

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“…The IVFR construction method is based on two constructors (called lower and upper constructors) in order to obtain the limits of each interval. In addition, it involves t-norms and t-conorms 17,18 which are well known generalizations of conjunction and disjunctions in classical logic. Definitions 3.1, 3.2 and 3.3 establish the basic method to construct an IVFR.…”

Section: Construction Of Ivfrmentioning

confidence: 99%

“…ThereInternational Journal of Computational Intelligence Systems, Vol. 8, Supplement 2 (2015), [16][17][18][19][20][21][22][23][24][25][26][27] Co-published by Atlantis Press and Taylor & Francis Copyright: the authors 16 fore, edge detection refers to the process of locating discontinuities in an image. 1 There are many different approaches to edge detection with the aim to extract contour features.…”

Section: Introductionmentioning

confidence: 99%

Gray Scale Edge Detection using Interval-Valued Fuzzy Relations

Bouchet¹,

Quirós²,

Alonso³

et al. 2015

IJCIS

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Gray scale edge detection can be modeled using Fuzzy Sets and, in particular, Interval-Valued Fuzzy Sets. This work is focused on studying the performance of several Interval-Valued Fuzzy Sets construction methods for detecting edges in a gray scale image. These construction methods are based on considering information related to the neighborhood of each point. Thus, several construction methods are proposed and tested, showing the approach performing better.

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“…Other Archimedean copula families include those of Frank (1979) and Gumbel (1960), which are generated by the Laplace transforms of the log series distribution and positive stable distribution; see also Hougaard (2000).…”

Section: Estimation Procedures With Multivariate Competing Risks Datamentioning

confidence: 99%

A semiparametric random effects model for multivariate competing risks data

Scheike¹,

Sun²,

Zhang³

et al. 2010

Biometrika

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SUMMARYWe propose a semiparametric random effects model for multivariate competing risks data when the failures of a particular type are of interest. Under this model, the marginal cumulative incidence functions follow a generalized semiparametric additive model. The associations between the cause-specific failure times can be studied through dependence parameters of copula functions that are allowed to depend on cluster-level covariates. A cross-odds ratio-type measure is proposed to describe the associations between cause-specific failure times, and its relationship to the dependence parameters is explored. We develop a two-stage estimation procedure where the marginal models are estimated in the first stage and the dependence parameters are estimated in the second stage. The large sample properties of the proposed estimators are derived. The proposed procedures are applied to Danish twin data to model the cumulative incidence for the age of natural menopause and to investigate the association in the onset of natural menopause between monozygotic and dizygotic twins.

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On the simultaneous associativity ofF(x, y) andx+y−F(x, y)

Cited by 942 publications

References 8 publications

Application of Fuzzy Einstein Operator to Multi-Criteria Decision-Making for Selection of Wind Turbine Type with Nominal Power of 2000 K

Application of Fuzzy Einstein Operator to Multi-Criteria Decision-Making for Selection of Wind Turbine Type with Nominal Power of 2000 K

Gray Scale Edge Detection using Interval-Valued Fuzzy Relations

A semiparametric random effects model for multivariate competing risks data

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