Three practical criteria of comparison among ordinal preference aggregating rules

Pérez, Joaquín; Barba-Romero, Sergio

doi:10.1016/0377-2217(94)00012-2

Cited by 15 publications

(5 citation statements)

References 12 publications

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“…Conversely, a statistical method named Borda's rule (Pérez et al . ) is applied to aggregate for each sample its ordinal position with respect to different visual variables. A vector containing the aggregated rankings of all the samples is obtained in this manner.…”

Section: Methodsmentioning

confidence: 99%

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Interpretation of Fabric Tactile Perceptions through Visual Features for Textile Products

Xue

Zeng

Koehl

et al. 2016

Journal of Sensory Studies

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In this article, a systematic method based on two sensory experiments has been proposed to explore the relations between the visual and haptic perceptions of the tactile properties of a number of textile samples. The first experiment is designed to investigate to what extent fabric tactile properties could be perceived through the samples' visual representations. On this basis, the second experiment is carried out to study the mathematical relation between different sensory (visual and tactile) datasets. In this study, a new approach has been proposed based on rough inclusion degree and fuzzy inference system to deal with the sensory relations. The results show that for the discussed samples, most fabric tactile properties could be well perceived via vision. With the help of a fuzzy neural model, it is possible to predict a certain tactile property from the numerical scores of its principal visual features. PRACTICAL APPLICATIONSCompared with researches focused on the development of mechanical simulative devices, the approach proposed here is much less expensive and could provide more direct and reasonable interpretation of fabric tactile information as both two sides of the model are from sensory systems which work as a whole during perception. Based on our model, with the help of image processing techniques, visual attributes will be automatically extracted from static or dynamic images, and interpreted by our rules to fabric tactile properties. Besides, this study will serve as a fundamental to the study on virtual fitting technologies in that the manufacturers or designers will be able to actively manipulate the virtual displays of textile products to provide our consumers with the most close-to-real sense of fabric.

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Section: Methodsmentioning

confidence: 99%

“…A novel approach based on the fusion of rough sets (Pawlak ), fuzzy inference (Dubois et al . ; Takagi and Sugeno ), fuzzy neural network (Jang ), and statistical methods (Siegel ; Pérez and Barba‐Romero ) is proposed to explore the relations between different sensory information.…”

Section: Introductionmentioning

confidence: 99%

Interpretation of Fabric Tactile Perceptions through Visual Features for Textile Products

Xue

Zeng

Koehl

et al. 2016

Journal of Sensory Studies

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“…For example, BAK implicitly assumes that DMs are able to rank all alternatives from first to last despite findings that such all-at-once comparisons can be quite difficult for many people (Jensen, 1986). Perez and Barba-Romero (1995) proposed three criteria: the frequency/intensity of internal consistencies, the ability to discriminate the best alternatives, and the complexity of the algorithms.…”

Section: The Study and Resultsmentioning

confidence: 99%

Examination of the similarity between a new Sigmoid function-based consensus ranking method and four commonly-used algorithms

Tavana

LoPinto

Smither

2008

IJOR

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The problem of aggregating individual rankings to create an overall consensus ranking representative of the group is of longstanding interest in group decision making. The problem arises in situations where a group of k Decision Makers (DMs) are asked to rank order n alternatives. The question is how to combine the DMs' rankings into one consensus ranking. Several different approaches have been suggested to aggregate DM responses into a compromise or consensus ranking, however, none is generally recognised as being the best and the similarity of consensus rankings generated by these algorithms is largely unknown. In this paper, we propose a new Weighted-sum ordinal Consensus ranking Method (WCM) with the weights derived from a Sigmoid function. We run Monte Carlo simulation across a range of k and n to compare the similarity of the consensus rankings generated by our method with the best-known method of Borda-Kendall (BAK; Kendall, M. (1962) Rank correlation methods. New York, NY: Hafner) and two other commonly used techniques proposed by Beck, M.P. and Lin, B.W. (1983) 'Some heuristics for the consensus ranking problem',

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“…The simplest but weakest measure on the alternatives x 1 , F F F ,x m under the criterion C k is the ordinal ranking based on z k x 1 , F F F ,z k x m X These ordinal rankings under the p criteria can be used to choose between any two alternatives x i and x j [15]. Let Cx i , x j fk:x i ranks better than x j under the criterion C k g and jCx i , x j j denotes the number of criteria in Cx i , x j X If each criterion is counted as one vote, then the jCx i , x j j is the number of votes supporting x i in the binary choice among x i and x j X When jCx i , x j j b pa2, the alternative x i has majority support of the p criteria and is selected over x j by majority consensus.…”

Section: Weights As Vote Values In Binary Choicesmentioning

confidence: 99%

Interpretation of criteria weights in multicriteria decision making

Choo

Schoner

Wedley

1999

Computers & Industrial Engineering

231

125

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Three practical criteria of comparison among ordinal preference aggregating rules

Cited by 15 publications

References 12 publications

Interpretation of Fabric Tactile Perceptions through Visual Features for Textile Products

Interpretation of Fabric Tactile Perceptions through Visual Features for Textile Products

Examination of the similarity between a new Sigmoid function-based consensus ranking method and four commonly-used algorithms

Interpretation of criteria weights in multicriteria decision making

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