Pattern recognition using type-II fuzzy sets

Mitchell, H. B.

doi:10.1016/j.ins.2004.02.027

Cited by 212 publications

(81 citation statements)

References 23 publications

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“…These weights that are based on the words can be further used in the evaluation based on perceptual computing. Several similarity measures are introduced for IT2 (Bustince 2000;Gorzalczany 1987;Mitchell 2005;Mendel 2008, 2009). In this study we used the Jaccard similarity measure for IT2 FSs.…”

Section: It2 Fs Dematel Methodsmentioning

confidence: 99%

Type-2 fuzzy set extension of DEMATEL method combined with perceptual computing for decision making

Hosseini

Tarokh

2013

J Ind Eng Int

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Most decision making methods used to evaluate a system or demonstrate the weak and strength points are based on fuzzy sets and evaluate the criteria with words that are modeled with fuzzy sets. The ambiguity and vagueness of the words and different perceptions of a word are not considered in these methods. For this reason, the decision making methods that consider the perceptions of decision makers are desirable. Perceptual computing is a subjective judgment method that considers that words mean different things to different people. This method models words with interval type-2 fuzzy sets that consider the uncertainty of the words. Also, there are interrelations and dependency between the decision making criteria in the real world; therefore, using decision making methods that cannot consider these relations is not feasible in some situations. The Decision-Making Trail and Evaluation Laboratory (DEMATEL) method considers the interrelations between decision making criteria. The current study used the combination of DEMATEL and perceptual computing in order to improve the decision making methods. For this reason, the fuzzy DEMATEL method was extended into type-2 fuzzy sets in order to obtain the weights of dependent criteria based on the words. The application of the proposed method is presented for knowledge management evaluation criteria.

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Section: It2 Fs Dematel Methodsmentioning

confidence: 99%

Type-2 fuzzy set extension of DEMATEL method combined with perceptual computing for decision making

Hosseini

Tarokh

2013

J Ind Eng Int

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“…2) Similarity measures for interval and general type-2 fuzzy sets: A number of methods have been proposed for measuring the similarity of interval T2 FSs (e.g., [20], [21], [22] and [23]) and general T2 FSs (e.g., [24] and [25]). In [26] and [27] the Jaccard similarity coefficient is extended for use with interval T2 FSs.…”

Section: Similarity Measuresmentioning

confidence: 99%

Similarity based applications for data-driven concept and word models based on type-1 and type-2 fuzzy sets

Wagner

Miller

Garibaldi

2013

2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

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Abstract-In this paper we explore the practical application of the previously introduced approach [1] to generate fuzzy sets from interval-valued data. We demonstrate two specific example applications where we 1) generate type-1 fuzzy sets from intervalvalued survey data for both words (e.g., neutral, excellent) and concepts (e.g., ambience, food) and 2) generate zSlices based general type-2 fuzzy set valued data from multiple iterations of a survey. We highlight the need for the simultaneous rating of both concepts and words in order to maintain context (including timeliness) of the resulting models. Further, in both example applications, we demonstrate using the Jaccard similarity measure how similarity measures can be employed to both relate and attribute word models to concept models (e.g., excellent food) and compare different concepts directly for different contexts (e.g., ambience in venue A vs. ambience in venue B). We provide interpretations for the resulting word/concept models and similarity values and highlight their utility, for example, for the data-driven generation of linguistic descriptions of venues. Finally, we highlight remaining questions and challenges both in technical terms and in application terms.

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“…Starting from the work of Mitchell (see [94]), Mendel presented in [17] a new expression for IV similarities. In the same paper, Mendel posed the following open question: finding the possible connection (if there is one) between the similarity measure (3) and the expression that he proposes.…”

Section: Similaritymentioning

confidence: 99%