• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.639-649
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• 2010

In this paper, a definition of interval-valued fuzzy regular language (IVFRL) is proposed and their related properties studied. A model of finite automaton (DFA and NDFA) with interval-valued fuzzy transitions is proposed. Acceptance of interval-valued fuzzy regular language by the finite automaton (DFA and NDFA) with interval-valued fuzzy transitions are examined. Moreover, a definition of finite automaton (DFA and NDFA) with interval-valued fuzzy (final) states is proposed. Acceptance of interval-valued fuzzy regular language by the finite automaton (DFA and NDFA) with interval-valued fuzzy (final) states are also discussed. It is observed that, the model finite automaton (DFA and NDFA) with interval-valued fuzzy (final) states is more suitable than the model finite automaton (DFA and NDFA) with interval-valued fuzzy transitions for recognizing the interval-valued fuzzy regular language. In the end, interval-valued fuzzy regular expressions are defined. We can use the proposed interval-valued fuzzy regular expressions in lexical analysis.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.409-417
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• 2009

A definition of finite automaton (DFA and NDFA) with intuitionistic fuzzy (final) states is proposed. Acceptance of intuitionistic fuzzy regular language by the finite automaton (DFA and NDFA) with intuitionistic fuzzy (final) states are examined. It is found that the finite automaton (DFA and NDFA) with intuitionistic fuzzy (final) states is more suitable for recognizing intuitionistic fuzzy regular language than earlier model. The paper also gives an idea of intuitionistic fuzzy regular expressions through possible definitions.

• Journal of the Korean Institute of Intelligent Systems
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• v.1 no.3
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• pp.20-32
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• 1991

This study seeks a way a way of dealing with unformatted natural language considering fuzzy set theory. The goal of the study is to establish a framework of an effective language understanding system that is linked to language classification system This study has found that languate understanding is strongly influenced by the language classification. The understanding of language. This study shows that the precision of language classification depends upon the way of how the language is classified in advance. In this study, a fuzzy logic was used to improve the precision of language classification. It was considered that the fuzzy logic might be albe to distinctively classify nuatural language texts into pretinent homogenious groups where contents of the language were identical. Accordingly, in the study, it was expected that classification of language were precisely classified by the fuzzy logic. An experimentalsystems was designed to evaluate the performane of a natural language understanding system that was connected to a fuzzy language classification system. Finally, the experiment suggests that a successful language understanding should require an real time interaction between mem andmachine fuzzy provious language classification.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.1
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• pp.5-15
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• 1997

This paper mentions a fault tree analysis using not probability but natural language and fuzzy theory, Reliability estimate of each basic event and dependence level estimate among subsystems are expressed by linguistic terms. Analysis results are also expressed by natural language. The meaning of linguistic terms is expressed by a fuzzy set. In the presented analysis approach parametrized operations of fuzzy sets are considered so that analyst's subjectivity can be introduced into the analysis. This paper gives the Chernobyl accident as an example of the fuzzy fault tree analysis using linguistic terms.

• Spatial Information Research
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• v.7 no.2
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• pp.191-207
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• 1999

Data and information necessary for solving the spatial decision making problems are imperfect or inaccurate and most are described by natural language. In order to process these arts of information by the computer, the obscure linguistic value need to be described quantitatively to let and computer understand natural language used by humans. For this , the fuzzy set theory and the fuzzy logic are used representative methodology. So this paper describes the construction of the language model by the natural language that user easily can understand and the logical concepts and construction process for building the fuzzy inference mechanism. It makes possible to solve the space related decision making problems intellectually through structuring and inference used by the computer, in case of the evaluation concern or decision making problems are described inaccurate, based on the inaccurate or indistinct data and information.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.227-230
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• 2003

We can not distinguish semantism of the feature of the current language “big”, “small”, “beautiful”. But we study artificial linguistic interface work and convert natural language to digital binary linguistic theory, we should define the basical conversion process. When we utilize the sum of product fuzzy theory and the visible numerical value, we can establish reasoning rule of input language. Fuzzy theory should be converted to general resulting rule.

• Journal of information and communication convergence engineering
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• v.8 no.1
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• pp.19-22
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• 2010

A finger language helping hearing impaired people in communication A sign language helping hearing impaired people in communication is not popular to ordinary healthy people. In this paper, we propose a method for real-time sign language recognition from a vision system using color information and fuzzy clustering system. We use YCbCr color model and canny mask to decide the position of hands and the boundary lines. After extracting regions of two hands by applying 8-directional contour tracking algorithm and morphological information, the system uses FCM in classifying sign language signals. In experiment, the proposed method is proven to be sufficiently efficient.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.579-582
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• 2003

In this paper, we propose a 4-step inference method needed for constructing a natural language communication system. The method is used to obtain fuzzy quantifier Q′when QA is Fisr τ⇔ Q′(m′A) is mF is m"is τ is inferred (Q, Q′: quantifiers, A: fuzzy subject, m′, m": modifiers, y: fuzzy predicate, τ: truth qualifier). We show that Q′is resolved step by step for two types of Q, including a non-increasing type (few,...) and a non-decreasing type(most,...).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.270-273
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• 2001

In this paper, we proposed the intelligent navigation agent model for successive electronic commerce management. For allowing intelligence, we used fuzzy theory. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.333-336
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• 1996

The sign language is a method of communication for deaf person. For sign communication, sign language and manual alphabet are used continuously. In this paper is proposed a system which recognize Korean sign language(KSL) and Korean manual alphabet(KMA) continuously. For recognizing KSL and KMA, basic elements for sign language, namely, the 14 hand directions, 23 hand postures, and 14 hand orientations are used. At first, this system recognize current motion state using speed and change of speed in motion by state automata. Using state, basic element classifiers using Fuzzy Min-Max Neural Network and Fuzzy Rule are executed. Meaning of signed gesture is selected by using basic elements which was recognized.