• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• 한국수학교육학회지시리즈B:순수및응용수학
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• 제27권2호
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• pp.97-108
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• 2020

In this paper, we prove common fixed point theorems for two mappings by using simulation function on fuzzy metric spaces. We also deduce some consequences in modular metric spaces.

• 충청수학회지
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• 제26권3호
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• pp.557-569
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• 2013

In this paper we shall introduce the $f$-function in a set, and give some properties of $f$-function of a set. In particular, we establish a relation between $f$-function of a set and fuzzy equivalence relation. We also introduce the notion of $f$-homomorphism on a semigroup S, and prove the generalized fundamental homomorphism theorem of semigroup.

• 대한수학회논문집
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• 제22권4호
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• pp.513-526
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• 2007

In this paper, we give some new definitions of M-fuzzy metric spaces and we prove a common fixed point theorem for six mappings under the condition of compatible mappings of first or second type in two complete M-fuzzy metric spaces.

• 대한수학회논문집
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• 제24권1호
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• pp.17-27
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• 2009

In the present work, we introduce two types of compatible maps and prove a common fixed point theorem for such maps in Menger probabilistic metric spaces. Our result generalizes and extends many known results in metric spaces and fuzzy metric spaces.

• Journal of applied mathematics & informatics
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• 제30권1_2호
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• pp.265-278
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• 2012

In this work we have considered several common fixed point results in metric spaces for weak compatible mappings. By applications of these results we establish some fixed point theorems in fuzzy metric spaces.

• 대한수학회논문집
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• 제27권2호
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• pp.265-277
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• 2012

In this paper we establish two common fixed point theorems in fuzzy metric spaces. These theorems are generalisations of the Banach contraction mapping principle and the Kannan's fixed point theorem respectively in fuzzy metric spaces. Our result is also supported by examples.

• 대한수학회논문집
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• 제24권4호
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• pp.581-594
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• 2009

In this paper, we establish a common fixed point theorem in complete fuzzy metric spaces which generalizes some results in [9].

• 대한수학회논문집
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• 제23권1호
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• pp.111-124
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• 2008

In this paper, we give some fixed point theorems on fuzzy metric spaces with an implicit relation. Our results extend and generalize some fixed point theorems on complete fuzzy metric spaces by using a new technique.

• Journal of applied mathematics & informatics
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• 제20권1_2호
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• pp.523-533
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• 2006

In this paper we have a common fixed point theorem which is a generalization of result of [12] and we characterize the conditions for continuous self mappings S, T of complete fuzzy metric space (X, M, *) have a uniqe common fixed point in X.