• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.556-561
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• 2009

In this paper, we propose new method to calculate the distance between intuitionistic fuzzy sets(IFSs) based on the three dimensional representation of IFSs and analyze the relations of similarity measure and distance measure of IFSs. Finally, we apply the proposed measures to pattern recognitions.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.314-321
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• 1995

This paper discuss some properties of non-monotonic fuzzy measures of Ф -bounded variation. We show that there is an example of Ф such that $\beta$V(x, F) is a proper subspace of Ф$\beta$V(x, F) And also, we prove that Ф$\beta$V(x, F) is a real Banach space. Furthermore, we investigate some properties of non-monotonic fuzzy Ф -measures.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.175-178
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• 2007

We give a geometrical interpretation of the interval-valued fuzzy set. So, based on the geometrical background, we propose new distance measures between interval-valued fuzzy sets and compare these measures with distance measures proposed by Burillo and Bustince and Grzegorzewski, respectively. Furthermore, we extend three methods for measuring distances between interval-valued fuzzy sets to interval-valued intuitionistic fuzzy sets.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.787-790
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• 1997

This paper proposes a method which selects essential elements in a human evaluation model using the Choquet integral based on fuzzy measures, and applies the model to the evaluation of human interface. Three kinds of concepts are defined to select essential elements. Increment Degree implies the increment degree from fuzzy measures of composed elements to the fuzzy measure of a combined element. Average of Increment Degree of an element means the relative possibility of superadditivity of the fuzzy measure of each combined element. Necessity Degree means the selection degree of each combined element as a result of the human evaluation. A task experiment, which consists of a static work and two dynamic works, is performed by the use of some human interfaces. In the experiment, (1) a warning sound which gives an attention to subjects, (2) a color vision which can be distinguished easily or not, (3) the size of working area and (4) a response of confirmation that is given from an interface, are considered as human interface elements. Subjects answer the questionnaire after the experiment. From the data of the questionnaire, fuzzy measures are identified and are applied to the proposed model. Effectiveness of the proposed model is confirmed by the comparison of human interface elements extracted from the proposed model and those from the questionnaire.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.31-36
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• 1998

This paper proposes a method to select essential elements in a human evaluation model using the Choquet integral based on fuzzy measures and applies the model to the evaluation of human interface. Three kinds of concepts, Increment Degree, average of Increment Degree, Necessity coefficient, are defined. The proposed method selects essential elements by the use of the Relative necessity coefficient. The proposed method is applied to the analysis of human interface. In the experiment, (1) a warning sound, (2)a color vision, (3) the size of working area, (4) a response of confirmation, are considered as human interface elements. subjects answer the questionnarie after the experiment. From the data of questionnaire, fuzzy measures are identified and are applied to the proposed model. effectiveness of the proposed model is confirmed by the comparison of human interface elements extracted from the proposed model and those from the questionnarie.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.264-267
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• 1998

We are dealing with the preliminary diagnosis from the information of headache interview chart. We quantify the qualitative information based on the interview chart by dual scaling. Prototype of fuzzy diagnostic sets and the neural linear regression methods are established with these quantified data, These new methods can be used to classify new patient's tone of diseases with certain degrees of belief and its concerned symptoms. We call these procedures as neural Fuzzy Differential Diagnosis of Headache (NFDDH-1). Also we investigate three measures to medical diagnosis, where relations between symptoms and diseases are described by intutionistic fuzzy set (IFS) data. Two measures are described by nin-max and max-min IFS operators, respectively. Another measure is the similarity degree, i.e., IFS distance between patient's symptoms and prototypes of diseases. We consider some reasonable criteria for three measures in order to determine the label of headache, We will establish hree measures in NFDDH-2 and combine two packages as NFDDH

• Journal of applied mathematics & informatics
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• v.20 no.1_2
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• pp.549-556
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• 2006

In this paper, we consider interval-valued Choquet integrals and fuzzy measures. Using these properties, we discuss some applications of them in multicriteria decision aid. In particular, we show how these interval-valued Choquet integrals can model behavioral analysis of aggregation in ulticriteria decision aid.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.1-3
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• 2001

In this paper, we define the convergence in measure and convergence in distribution for set-valued Choquet integrals. Using there definitions, we discuss convergence theorems for set-valued Choquet integrals.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.271-280
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• 1996

This paper presents an evaluation method on enterprise using fuzzy integral which is defined by fuzzy measures. The weight of criteria is computed by eigenvector method. And, using this calculated weight, the total evaluation value is obtained from the weight of by means of Pl & Bel measures. This value means the level on enterprise's situation considering from the viewpoint of evaluation factors.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.502-506
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• 2013

The cash flow forecasting is normally done by contractors in construction industry at early stages of the project for contractual decisions. The decision making in such situations involve uncertainty about future cash flows and assessment of working capital requirements gains more importance in projects constrained by cash. The traditional approach to assess the working capital requirements is deterministic in and neglects the uncertainty. This paper presents an alternate approach to assessment of working capital requirements for contractor based on fuzzy set theory by considering the uncertainty and ambiguity involved at payment periods. Statistical methods are used to deal with the uncertainty for working capital curves. Membership functions of the fuzzy sets are developed based on these statistical measures. Advantage of fuzzy peak working capital requirements is demonstrated using peak working capital requirements curves. Fuzzy peak working capital requirements curves are compared with deterministic curves and the results are analyzed. Fuzzy weighted average methodology is proposed for the assessment of peak working capital requirements.