• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.949-952
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• 1993

As well-known, fuzzy control has been recognized to be of great usefulness in many engineering fields. However, the present design methods of fuzzy control systems depend on trial and error the thing that limits its usefulness. Therefore, an effective and convenient support tools for design and evaluation are greatly needed as well as the establishment of the design methods and guidling. From these backgrounds, we have developed a fuzzy control simulator[1, 2] which has various fuzzy control methods such as "direct method", "indirect method" and "fuzzy-PID method". This paper deals especially with the "direct method" function of the simulator. The simulator was developed for personal computers and programed in C language.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.85-91
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• 1995

This paper presents a system which recognizes the Korean Sign Language(KSL) and translates into normal Korean speech. A sign language is a method of communication for the deaf-mute who uses gestures, especially both hands and fingers. Since the human hands and fingers are not the same in physical dimension, the same form of a gesture produced by two signers with their hands may not produce the same numerical values when obtained through electronic sensors. In this paper, we propose a dynamic gesture recognition method based on feature analysis for efficient classification of hand motions, and on a fuzzy min-max neural network for on-line pattern recognition.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.107-117
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• 1992

Conventional fault tree analysis has several problems as the estimations and tolerances of the failure probability values. To overcome these problems, fuzzy concepts with natural language can be applied to conventional fault tree analysis. And, we propose the evaluation method of the imprecision of top/basic events and possibility importances of basic events.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.92-100
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• 1995

Fuzzy reasoning has been applied to analysis of traffic problems on urban arterial road. As the analysis on factors of route choice has been already carried out, its result can be used for construction of the model. Route choice rate estimation by fuzzy reasoning was discussed from its structure and accuracy. The major objective of the study is to introduce some kinds of methods with fuzzy reasoning and to make their feature obvious. First, the production system model is introduced with consideration of reality to actual travel behavior. Second, overlapping areas of fuzzy language function are investigated. Finally, process of fuzzy reasoning was also considered. Five kinds of Fuzzy reasoning are compared to investigate in relation between shapes of membership function and estimation validity.

• Korean Journal of Cognitive Science
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• v.2 no.2
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• pp.309-339
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• 1990

The most common way that people communicate is by speaking or writing natural languages.But if people use computers in the modern technology,they should learn artificial programming languages.If computers could understand what people mean when people speak or type natural languages,people would use the computers more easily and naturally.but there is a problem.The language which people use has vagueness.For example,the convential computer system cant's handle the subjective feeling like 'tall' or 'young'.So peole must specify the exact threshold like 'more'than 25 ages'.We have developed the knowledge-based natural language question answering system which can handle sentences having fuzzy concepts by using blackboard model.Our goal of this research is to develop a portable question answering system as interface for database systems or understanding systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.53-62
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• 2008

Cross-lingual text retrieval(CLTR) is the information retrieval in which a user tries to search a set of documents written in one language for a query another language. This thesis proposes a CLTR system based on fuzzy multilingual thesaurus to handle a partial matching between terms of two different languages. The proposed CLTR system uses a fuzzy term matrix defined in our thesis to perform the information retrieval effectively. In the defined fuzzy term matrix, all relation degrees between terms are inferred from using the transitive closure algorithm to reflect all implicit links between terms into processing of the information retrieval. With this framework, the CLTR system proposed in our thesis enhances the retrieval effectiveness because it is able to emulate a human expert's decision making well in CLTR.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.6 no.3
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• pp.265-269
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• 2005

A fuzzy query language, called FSQL, in the relational databases is introduced in this paper. In general, database systems have query systems which are able to retrieve and manipulate precise data. However, such queries are hard to operate on the real world applications since their queries are often imprecise or incomplete. Recently, considerable attention has been given to research dealing with vagueness of the query in relational database systems. In this paper we have suggested an effective method of accepting vagueness of the query in data processing. The syntax of FSQL is formally defined with EBNF, and an interpreter of FSQL has been implemented as a prototype.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• Proceedings of the Korean Society for Language and Information Conference
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• 1996.02a
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• pp.337-346
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• 1996

• Proceedings of the KIEE Conference
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• 2001.11c
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• pp.76-79
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• 2001

This paper is concerned with a stability analysis of Madam Type fuzzy systems. It Introduces the canonical form of an unforced fuzzy system and its stability theorem suggested in the previous study. Then it gives new simplified stability conditions based on the Lyapunov function method. A common positive definite matrix in the stability conditions is searched by the LMI method.