• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.40.6-40
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• 2001

Fuzzy controls are widely used in industrial fields using experts knowledge base for its high degree of performance. Genetic Algorithm(GA) is one of the numerical method that has an advantage of optimization. In this paper, we present an acquisition method of fuzzy rules using genetic algorithm. Knowledge of the system is the key to generating the control rules. As these rules, a system can be more stable and it reaches the control goal the faster. To get the optimal fuzzy control rules and the membership functions, we use the GA instead of the experts knowledge base. Information of the system is coded the chromosome with suitable phenotype. Then, it is operated by genetic operator, and evaluated by evaluation function. Passing by the decoding process with the fittest chromosome, the genetic algorithm can tune the fuzzy rules and the membership functions automatically ...

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.27-32
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• 2012

In this paper, we propose a fuzzy method that improves the existing problem of the fuzzy filtering algorithm. The proposed fuzzy filtering algorithm separates R, G, and B channels from the color image. Mask information was extracted from separated channels and the brightness of the mean value and median value for channels was applied in the function of the proposed fuzzy method to calculate the membership and achieve application in the inference rule. Also, the membership degrees of R, G, and B were used to distinguish the possibility of noise. The proposed fuzzy method selected three membership functions. If noise is distinguished, the noise is eliminated by selecting the median value or mean value as the relevant pixel value according to the degree of noise. By applying the proposed method in color images, it was verified that the proposed method is more effective in eliminating noise when compared with the conventional fuzzy filtering method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.327-332
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• 1996

Rough Set theory suggested by Pawlak has a property that it can describe the degree of relation between condition and decision attributes of data which don't have linguistic information. In this paper, by using this ability of rough set theory, we define a occupancy degree which is a measure can represent a degree of relational quantity between condition and decision attributes of data table. We also propose a method that can find an optimal fuzzy rule table and membership functions of input and output variables from data without linguistic information and examine the validity of the method by modeling data generated by fuzzy rule.

• Korean Business Review
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• v.17 no.2
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• pp.161-183
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• 2004

This research is to examine the effect of specific Sports On-line membership characteristics on Customer loyalty, the role of the important concept of the three degree of commitment(Continuance commitment, Normative commitment, Affective commitment) in relation marketing. First, discover whether professional team's customer loyalty is influenced by Sports on-line membership through the three degrees of commitment, which is an important parameter in customer relation. Second, find out the effect of currently used online membership characteristics of an off-line company on the three degrees of commitment. To achieve this aim our research team carried out an empirical study by creating an experimental hypothesis and model. The research was conducted by an online survey by 211 supporters of professional football teams. Out of the total 23 were judged untrustworthy by double answers, the empirical study was drawn out from the remaining 188. The empirical study was done by statistical analysis programs SPSS 10.0 and AMOS 4.0. The conclusion of this research is that specific characteristics of Sports on-line membership, Continuance commitment, Normative commitment, Affective commitment plays an important role as a medium in Customer loyalty.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.301-309
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• 2006

In this paper, we show the improved fuzzy c-means clustering method. To improve, we use the double clustering as principal component analysis from objects which is located on common region of more than two clusters. In addition we use the degree of membership (probability) of fuzzy c-means which is the advantage. From simulation result, we find some improvement of accuracy in data of the probability 0.7 exterior and interior of overlapped area.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.506-511
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• 1998

In this paper we consider multiobjective linear programming problems with coefficients of the objective functions specified by possibility distributions. Possibly and necessarily efficient solution sets are defined as funny solution sets whose membership grades represent possibility and necessity degrees to which a feasible solution is efficient. Considering efficiency condition and its dual condition in ordinary multiobjective linear programming problem, we propose efficiency test methods based on an extreme ray generation method. Since the proposed methods can be put in the part of a bi-section method, we can develop calculation and methods of the degree of possible and necessary efficiency for feasible solutions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.232-239
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• 2006

This paper is for applying interactive fuzzy linear programming for the problem of product mix planning, which is one of the aggregate planning problem. We developed a modified algorithm, which has two-phase approach for interactive fuzzy linear programming to get a better solution. Adding two-phase method, we expect to obtain not only the highest membership degree, but also a better utilization of each constrained resource.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.4
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• pp.259-262
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• 2010

Study about fuzzy entropy and similarity measure on intuitionistic fuzzy sets (IFSs) were proposed, and analyzed. Unlike fuzzy set, IFSs contains uncertainty named hesistancy, which is contained in fuzzy membership function itself. Hence, designing fuzzy entropy is not easy because of ununified entropy definition. By considering different fuzzy entropy definitions, fuzzy entropy is designed and discussed their relation. Similarity measure was also presented and verified its usefulness to evaluate degree of similarity.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.52-58
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• 1995

A shared-weight neural network that performed classification based on the features extracted with the fuzzy morphological operation is introduced. Learning rules for the structuring elements, degree of membership, and weighting factors are also precisely described. In application to handwritten digit recognition problem, the fuzzy morphological shared-weight neural network produced the results which are comparable to the state-of-art for this problem.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1997.11a
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• pp.105-116
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• 1997

The fuzzy logic controller was used effectively for the controlling of unmeasured parameter and inaccurate mathematical modeling was designed. In this paper, we proposed that the method of reducing the vibration at the target point on calculating the membership degree about input value without a look-up table was proposed. And its effectiveness in the inverted pendulum was acquired.