The problem of linguistic approximation in clinical decision making

Degani, R.; Bortolan, G.

doi:10.1016/0888-613x(88)90105-3

Cited by 282 publications

(75 citation statements)

References 11 publications

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“…Therefore, we can apply fuzzy membership function approach for transforming linguistic beliefs into numbers in interval scale. The applicability of such approach have become more and more clear for the users of important fields as such as information retrieval (Bordogna and Pasi [23], medical information gathering and retrieval (Degani and Bortolan [24], education (Law [25], suppliers selection (Herrera [18,19]), and decision making, in general.…”

Section: Fuzzy Sets and Arithmetic Operationsmentioning

confidence: 99%

Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets

Mehrjerdi¹

2012

IJCA

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Ranking competing alternatives in terms of their overall performance with respect to some criterions in fuzzy environment is possible by the use of fuzzy TOPSIS methodology using interval-valued fuzzy-sets concepts. This author presents an effective fuzzy multi-criteria method based upon the fuzzy model and the concepts of positive ideal and negative ideal solution points for prioritizing alternatives using inputs from a team of decision makers. The fuzzy sets concepts are used to evaluate the performance of alternatives and the importance of criteria. Fuzzy TOPSIS based on the interval-valued fuzzy-sets is fully described and a case study on RFID comprised of four main criteria and five alternatives is constructed and solved by the proposed extended TOPSIS method. The TOPSIS methodology used in this article is able to grasp the ambiguity exists in the utilized information and the fuzziness appears in the human judgments and preferences. TOPSIS technique can easily produce satisfactory results, and hence stimulates creativity and the invention for developing new methods and alternative approaches. This article is a very useful source of information for Fuzzy TOPSIS based on the interval-valued fuzzy sets and extends the area of application of RFID technology in general. Due to the fact that a better management of a system is related to the full understanding of the technologies implemented and the system under consideration, sufficient background on the methodologies are provided and a case study is developed and solved by the proposed method.

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Section: Fuzzy Sets and Arithmetic Operationsmentioning

confidence: 99%

Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets

Mehrjerdi¹

2012

IJCA

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“…There exist different computational models to accomplish them. Classical CW models are those based on the Extension principle 11 and symbolic one 12 . Both of them produce a loss of information in their computations 11,12 and hence a lack of precision in the results.…”

Section: -Tuple Linguistic Representation Modelmentioning

confidence: 99%

“…Classical CW models are those based on the Extension principle 11 and symbolic one 12 . Both of them produce a loss of information in their computations 11,12 and hence a lack of precision in the results. Linguistic computational model 19 based on linguistic 2-tuples carries out processes of CW in a precise way when the linguistic term sets are symmetrical and uniformly distributed.…”

Section: -Tuple Linguistic Representation Modelmentioning

confidence: 99%

A Linguistic Multigranular Sensory Evaluation Model for Olive Oil

Martínez¹,

Espinilla²,

Pérez³

2008

IJCIS

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Evaluation is a process that analyzes elements in order to achieve different objectives such as quality inspection, marketing and other fields in industrial companies. This paper focuses on sensory evaluation where the evaluated items are assessed by a panel of experts according to the knowledge acquired via human senses. In these evaluation processes the information provided by the experts implies uncertainty, vagueness and imprecision. The use of the Fuzzy Linguistic Approach 32 has provided successful results modelling such a type of information. In sensory evaluation it may happen that the panel of experts have more or less degree knowledge of about the evaluated items or indicators. So, it seems suitable that each expert could express their preferences in different linguistic term sets based on their own knowledge. In this paper, we present a sensory evaluation model that manages multigranular linguistic evaluation framework based on a decision analysis scheme. This model will be applied to the sensory evaluation process of Olive Oil.

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“…For dealing with the linguistic information in the decision making, there have been several methods for aggregate linguistic information: extension principle [2], symbolic method [3], linguistic scale method [4], 2-tuple linguistic representation model [5]. The minimum like tnorms, copulas and quasi-copulas, the maximum like tconorms, dual quasi-copulas, dual copulas, between minimum and maximum like means, weighted means [6], the lexmax (Discrimax) and lexmin (Discrimin) methods [7] and so on.…”

Section: Introductionmentioning

confidence: 99%

Linguistic information aggregation operator and its application in multi-attribute group decision making

Lan¹,

Lu²,

Mo³

et al. 2015

Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering

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Abstract-This paper proposes a new method to deal with the multi-attribute group decision making (MAGDM) problem. Firstly, a new distance measure between two linguistic terms is defined, then a new linguistic information aggregation operator based on the distance measure is proposed and their properties are studied. Secondly, in order to deal with multi-attribute group decision making problem under linguistic environment, a similarity measure between two linguistic preference matrices is proposed. The aggregation operator and the similarity measure are applied to a MAGDM problem. Finally, a numerical example is proposed to prove that the new operator is effective in the MAGDM problems. This method avoid the case that a numerical value times a linguistic information and the results of evaluation are still belongs to the original linguistic term set no matter how to calculate. By using the supporting of the order, the linguistic information can not be lose in the aggregation process.

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The problem of linguistic approximation in clinical decision making

Cited by 282 publications

References 11 publications

Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets

Developing Fuzzy TOPSIS Method based on Interval-valued Fuzzy Sets

A Linguistic Multigranular Sensory Evaluation Model for Olive Oil

Linguistic information aggregation operator and its application in multi-attribute group decision making

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