CC-separation Measure Applied in Business Group Decision Making

Wieczynski, Jonata; Lucca, Giancarlo; Borges, Eduardo Nunes; Dimuro, Graçaliz Pereira; Lourenzutti, Rodolfo; Bustince, Humberto

doi:10.5220/0010439304520462

Cited by 10 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For the analysis of the results from the different copula functions, we use two different approaches. The first one is by using the Big Delta [28], defined bellow, to see which copula function gives the biggest difference between rankings first and second.…”

Section: Methodsmentioning

confidence: 99%

“…This is the step where this study incorporates the CC-integrals in place of the Choquet integral. We remind the definition of the CC-separation measure by: Definition 1 (CC-separation measure [28]). Let Co be a bivariate copula and m a fuzzy measure.…”

Section: Generalization Of the Gmc-rtopsis By Using Cc-integralsmentioning

confidence: 99%

“…In this paper, we expand the analysis of the CC-separation measure study [28] by increasing the number of CC-integrals analyzed, elevating the 11 from the previews article to 30 in this one. We, again, apply the CC-integrals in an application as an example, the same used in [15,27,28]. To better visualize the analysis by using the ∆ R1,R2 difference we plotted it for each of the 30 different CC-integrals.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Application and Comparison of CC-Integrals in Business Group Decision Making

Wieczynski,

Lucca,

Borges

et al. 2022

Lecture Notes in Business Information Processing

Self Cite

View full text Add to dashboard Cite

Optimized decisions is required by businesses (analysts) if they want to stay open. Even thought some of these are from the knowhow of the managers/executives, most of them can be described mathematically and solved (semi)-optimally by computers. The Group Modular Choquet Random Technique for Order of Preference by Similarity to Ideal Solution (GMC-RTOPSIS) is a Multi-Criteria Decision Making (MCDM) that was developed as a method to optimize the later types of problems, by being able to work with multiple heterogeneous data types and interaction among different criteria. On the other hand the Choquet integral is widely used in various fields, such as brain-computer interfaces and classification problems. With the introduction of the CC-integrals, this study presents the GMC-RTOPSIS method with CC-integrals. We applied 30 different CC-integrals in the method and analyzed its results using 3 different methods. We found that by modifying the decisionmaking method we allow for more flexibility and certainty in the choosing process.

show abstract

Section: Methodsmentioning

confidence: 99%

Section: Generalization Of the Gmc-rtopsis By Using Cc-integralsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Application and Comparison of CC-Integrals in Business Group Decision Making

Wieczynski,

Lucca,

Borges

et al. 2022

Lecture Notes in Business Information Processing

Self Cite

View full text Add to dashboard Cite

show abstract

“…Similarly, the C T -integral can be applied to multi-criteria decision-making problems; see [17]. Other generalizations of the Choquet integral have seen use in problems involving multi-criteria decision-making (see [18,19]). In this paper, we focus on multi-criteria decision-making problems.…”

Section: Introductionmentioning

confidence: 99%

CT-Integral on Interval-Valued Sugeno Probability Measure and Its Application in Multi-Criteria Decision-Making Problems

Hong

Shang

Gong

2022

Axioms

View full text Add to dashboard Cite

It is well known that the complexity of the decision-making environment frequently coexists with the diversity of linguistic information in the decision-making process. In order to solve this kind of uncertain multi-criteria decision-making problem, reasonable measures and integrals should be established. In this paper, the discrete expression of the CT-integral on the interval-valued Sugeno probability measure is proposed. The CT-integral is the Choquet integral when the t-norm is T(x,y)=xy in the CT-integral and is a pre-aggregation function. Then, the CT-integral on interval-valued Sugeno probability measure is applied to solve end-of-life (EOL) strategy in order to determine multi-criteria decision-making problems. Compared with the general Choquet integral, the method proposed in this paper significantly improves the calculation process, that is, the calculation is simpler and the amount of calculation is smaller. A case study was performed in order to validate the effectiveness of this conclusion.

show abstract

“…These advances in generalizing the standard Choquet integral, aiming at restricting the requirements of the functions being used in their constructions and also relaxing the monotonicity of the integral, were applied with success in the FRM of FR-BCS. C T -and CC-integral were also applied to multi-criteria decision making problems [24], [25] and image processing [26].…”

Section: Introductionmentioning

confidence: 99%

Applying d-XChoquet integrals in classification problems

Wieczynski

Lucca

Borges

et al. 2022

2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

Self Cite

View full text Add to dashboard Cite

Several generalizations of the Choquet integral have been applied in the Fuzzy Reasoning Method (FRM) of Fuzzy Rule-Based Classification Systems (FRBCS's) to improve its performance. Additionally, to achieve that goal, researchers have searched for new ways to provide more flexibility to those generalizations, by restricting the requirements of the functions being used in their constructions and relaxing the monotonicity of the integral. This is the case of CT-integrals, CC-integrals, CF-integrals, CF1F2-integrals and dCF-integrals, which obtained good performance in classification algorithms, more specifically, in the fuzzy association rule-based classification method for high-dimensional problems (FARC-HD). Thereafter, with the introduction of Choquet integrals based on restricted dissimilarity functions (RDFs) in place of the standard difference, a new generalization was made possible: the d-XChoquet (d-XC) integrals, which are ordered directional increasing functions and, depending on the adopted RDF, may also be a pre-aggregation function. Those integrals were applied in multi-criteria decision making problems and also in a motor-imagery brain computer interface framework. In the present paper, we introduce a new FRM based on the d-XC integral family, analyzing its performance by applying it to 33 different datasets from the literature.

show abstract

CC-separation Measure Applied in Business Group Decision Making

Cited by 10 publications

References 0 publications

Application and Comparison of CC-Integrals in Business Group Decision Making

Application and Comparison of CC-Integrals in Business Group Decision Making

CT-Integral on Interval-Valued Sugeno Probability Measure and Its Application in Multi-Criteria Decision-Making Problems

Applying d-XChoquet integrals in classification problems

Contact Info

Product

Resources

About