• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.176-181
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• 2004

This paper introduces a Web site login system that uses user's native voice to improve the bother of remembering the ID and password in order to login the Web site. The DTW method that applies fuzzy inference is used as the speaker recognition algorithm. We get the ACC(Average Cepstrum Coefficient) membership function by each degree, by using the LPC that models the vocal chords, to block the recorded voice that is problem for the speaker recognition. We infer the existence of the recorded voice by setting on the basis of the number of zeros that is the value of the ACC membership function, and on the basis of the average value of the ACC membership function. We experiment the six Web sites for the six subjects and get the result that protects the recorded voice about 98% that is recorded by the digital recorder.

• Journal of Radiation Protection and Research
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• v.14 no.1
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• pp.71-74
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• 1989

A statistical model for the relation between KARP membership and articles published in the KARP Journal on the yearly basis was obtained by using the least-squares method. From this, KARP membership potent to publish the KARP Journal up to 4 numbers a year were projected. It is revealed that at least 650 KARP members are needed.

• The Journal of Fisheries Business Administration
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• v.48 no.1
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• pp.17-29
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• 2017

The primary purpose of this paper is to analyze the membership of fishing community. In order to become a member of fishing community, some conditions are needed both the member of local fisheries cooperatives and resident of fishing village. Generally, many fishing communities have additional conditions such as to be a member of fishing community that is a minimum term of residence, an entrance fee, fishing abilities. These additional conditions play a critical role in making a relationship, building trust and enhancing fairness. However, the setting of excessive additional conditions make it possible to obstruct growth of fishing community.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.298-309
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• 2004

In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple overlapping membership functions, which is a typical feature of unconstrained optimization, is resolved with the help of the proposed fitness function. The proposed algorithm can generate a fuzzy model with transparent membership functions. Through simulations on various problems, the proposed algorithm found a TSK fuzzy model with better accuracy than those found in previous works with transparent partition of input space.

• Proceedings of the IEEK Conference
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• summer
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• pp.447-450
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• 2004

This paper proposes remotely sensed image classification method by fuzzy c-means clustering algorithm using average intra-cluster distance. The average intra-cluster distance acquires an average of the vector set belong to each cluster and proportionates to its size and density. We perform classification according to pixel's membership grade by cluster center of fuzzy c-means clustering using the mean-values of training data about each class. Fuzzy c-means algorithm considered membership degree for inter-cluster of each class. And then, we validate degree of overlap between clusters. A pixel which has a high degree of overlap applies to the maximum likelihood classification method. Finally, we decide category by comparing with fuzzy membership degree and likelihood rate. The proposed method is applied to IKONOS remote sensing satellite image for the verifying test.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1626-1629
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• 2002

This paper describes novel methods to construct fuzzy inference rules with gradient descent. The present methods have a constructive mechanism of the rule unit that is applicable in two parameters: the central value and the width of the membership function in the antecedent part. The first approach is to create the rule unit at the nearest position from the input space, for the central value of the membership function in the antecedent part. The second is to create the rule unit which has the minimum width, for the width of the membership function in the antecedent part. Experimental results are presented in order to show that the proposed methods are effective in difference on the inference error and the number of learning iterations.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.7-10
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• 1998

The conventional relational databases have difficulties to efficiently represent various of data because an attribute of a tuple should have only one elementary value. In order to represent ambiguous and imprecious information, fuzzy set and rough set have been gaining acceptance, especially as a tool for knowledge discovery in databases. One of former researches applies only one fuzzy membership value to a tuple. We suggest a more advanced model for data representation by way of applying many membership values to a tuple, i.e. one membership value to each attribute of a tuple.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.297-300
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• 2005

In this study, we proposed genetically optimized self-organizing fuzzy polynomial neural network based on information granulation and evolutionary algorithm (gdSOFPNN), develop a comprehensive design methodology involving mechanisms of genetic optimization. The proposed gdSOFPNN gives rise to a structural Iy and parametrically optimized network through an optimal parameters design available within FPN (viz. the number of input variables, the order of the polynomial, input variables, the number of membership functions, and the apexes of membership function). Here, with the aid of the information granulation, we determine the initial location (apexes) of membership functions and initial values of polynomial function being used in the premised and consequence part of the fuzzy rules respectively. The performance of the proposed gdSOFPNN is quantified through experimentation that exploits standard data already used in fuzzy modeling.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.720-725
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• 2001

Derivation of TSK fuzzy model from nonlinear differential equation is fundamental issue in the field of theoretical fuzzy control. The method which does not yield affine local differential equations at off-equilibrium points is proposed in this paper. A prototype TSK fuzzy model which has triangular membership functions for linguistic terms of the antecedent part is derived systematically. And then GA is used to modify the membership functions optimally. Simulation results show the validity of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.145-149
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• 2008

The similarity measure is constructed for non-convex fuzzy membership function using well known Hamming distance measure. Comparison with convex fuzzy membership function is carried out, furthermore characteristic analysis for non-convex function are also illustrated. Proposed similarity measure is proved and the usefulness is verified through example. In example, usefulness of proposed similarity is pointed out.