• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.145-154
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• 1999

An intelligent system embedded with multiple sources of knowledge may provide more robust intelligence with highly ill structured problems than the system with a single source of knowledge. This paper proposes the hybrid knowledge integration mechanism that yields the cooperated knowledge by integrating expert, user, and machine knowledge within the fuzzy logic-driven framework, and then refines it with a genetic algorithm (GA) to enhance the reasoning performance. The proposed knowledge integration mechanism is applied for the prediction of Korea stock price index (KOSPI). Empirical results show that the proposed mechanism can make an intelligent system with the more adaptable and robust intelligence.

• 한국지능시스템학회논문지
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• 제12권4호
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• pp.289-293
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• 2002

분류자 시스템(Classifier System)은 유전자 알고리즘(Genetic Algorithmsm : GA)을 이용하여 새로운 규칙 집합을 발견하는 시스템이다 또 로봇 축구 시뮬레이션 게 (SimuroSot)은 시간에 따라 상태가 변화하는 동적인 시스템이다. 본 논문에서는 GBML(Genetic Based Machine Learning)의 한 갈래이자 미시간 접근 방법을 기반으로 하는 Zeroth Level Classifier System(ZCS)을 SimuroSot에 적용하여 게임 전략을 구성하는 새로운 규칙을 발견하고 학습하도록 하고 시뮬레이션 결과를 분석함으로써 ZCS의 유용성을 확인한다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 1989년도 한글날기념 학술대회 발표논문집
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• pp.126-131
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• 1989

본 논문에서는 Error Back Propagation 학습을 이용해 한글 문자를 On-Line 인식하는 시스템을 제안한다. Pointing device의 궤적을 추적해 입력 패턴의 특징(feature)을 추출해 신경 회로망 입력으로 준다. 이때 사용하는 특징은 기본 획 (stroke)의 종류 및 획간의 상대적 위치 관계이다. 학습과정에서는 자소의 정의를 읽어 초성, 중성, 종성에 대해 각 획수마다 정의된 신경회로망의 weight를 조정한다. 인식 과정에서는 초성, 중성, 종성의 순으로 에러가 최소인 획수의 신경회로망 출력을 택하여 2 바이트 조합형 코드로 완성한다. 이로써 Intelligent Man-Machine Interface 시스템중 위치 및 크기에 무관한 전필 입력 시스템을 구현한다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
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• pp.272-277
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• 1998

If we want to compare the form of two objects, the human vision takes into account the parameter's width/length/height at the same time. however, the machine needs to compare width then lengths and finally height. In each comparison the machine considers only one character. The goal of this paper is to imitate the human manner of comparison and recognition by using two or three characters instead of one during the comparison. The ellipse is a first approach of comparison because it provides us a general and a simple relation that can link two parameters that are the half axis of the ellipse. Indeed, we assimilate each character to a half axis of the ellipse and the result is a geometrical figure that varies according to values of the two characters.

• 한국지능시스템학회논문지
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• 제11권6호
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• pp.549-557
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• 2001

Morphological analysis and POS tagging require a dictionary for the language at hand . In this fashion though it is impossible to analyze a language a dictionary. We also have difficulty if significant portion of the vocabulary is new or unknown . This paper explores the possibility of learning morphology of an agglutinative language. in particular Korean language, without any prior lexical knowledge of the language. We use unsupervised learning in that there is no instructor to guide the outcome of the learner, nor any tagged corpus. Here are the main characteristics of the approach: First. we use only raw corpus without any tags attached or any dictionary. Second, unlike many heuristics that are theoretically ungrounded, this method is based on statistical methods , which are widely accepted. The method is currently applied only to Korean language but since it is essentially language-neutral it can easily be adapted to other agglutinative languages.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2005년도 추계학술대회 학술발표 논문집 제15권 제2호
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• pp.135-138
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• 2005

Java Virtual Machine이 기반이 되는 플랫폼 사용으로 모바일 폰 Java는 C/C++로 컴파일 된 Binary File에 비해 속도가 떨어지고 고성능의 프로세서를 필요로 하기 때문에 가격이 비싸질 수밖에 없다. Native Binary를 사용하는 Nano-X Window System Graphic Engine은 저 사양 프로세서에서 사용가능한 모바일 플랫폼으로써 Java Virtual Machine 보다 빠른 속도를 구현할 수 있고 GPL License를 따르기 때문에 생산단가도 절약할 수 있어 저가형 핸드폰의 대량 생산으로 인해 현재 떠오르고 있는 신흥시장에서 보다 경쟁력을 높일 수 있을 것으로 기대된다. 본 논문에서는 기존의 모바일 플랫폼과 Nano-X window System을 비교해보고 모바일 플랫폼으로써의 개발 방향에 대해 논해 보려 한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권2호
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• pp.96-101
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• 2015

Support vector machine (SVM) has a strong theoretical foundation and also achieved excellent empirical success. It has been widely used in a variety of pattern recognition applications. Unfortunately, SVM also has the drawback that it is sensitive to outliers and its performance is degraded by their presence. In this paper, a new outlier detection method based on genetic algorithm (GA) is proposed for a robust SVM. The proposed method parallels the GA-based feature selection method and removes the outliers that would be considered as support vectors by the previous soft margin SVM. The proposed algorithm is applied to various data sets in the UCI repository to demonstrate its performance.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권2호
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• pp.125-130
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• 2016

The proposal of this study is a fast version of the conventional extreme learning machine (ELM), called pseudoinverse matrix decomposition based incremental ELM (PDI-ELM). One of the main problems in ELM is to determine the number of hidden nodes. In this study, the number of hidden nodes is automatically determined. The proposed model is an incremental version of ELM which adds neurons with the goal of minimization the error of the ELM network. To speed up the model the information of pseudoinverse from previous step is taken into account in the current iteration. To show the ability of the PDI-ELM, it is applied to few benchmark classification datasets in the University of California Irvine (UCI) repository. Compared to ELM learner and two other versions of incremental ELM, the proposed PDI-ELM is faster.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권3호
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• pp.204-210
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• 2011

This paper proposes a fuzzy support vector machine ($FSVM_n$) pattern classifier to classify the arrhythmia patterns of an electrocardiograph (ECG). The $FSVM_n$ is a pattern classifier which combines n-dimensional fuzzy membership functions with a slack variable of SVM. To evaluate the performance of the proposed classifier, the MIT/BIH ECG database, which is a standard database for evaluating arrhythmia detection, was used. The pattern classification experiment showed that, when classifying ECG into four patterns - NSR, VT, VF, and NSR, VT, and VF classification rate resulted in 99.42%, 99.00%, and 99.79%, respectively. As a result, the $FSVM_n$ shows better pattern classification performance than the existing SVM and FSVM algorithms.

• International Journal of Precision Engineering and Manufacturing
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• 제8권1호
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• pp.38-45
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• 2007

We propose a preprocessing method for removing floating particles from underwater images based on an analysis of the image features. We compared baseline JPEG and wavelet codec methods to determine the method best suited for underwater images. The proposed preprocessing method enhanced the compression ratio and resolution, and provided an efficient means of compressing the images. The wavelet codec method yielded better compression ratios and image resolutions. The results suggest that the wavelet codec method linked with the proposed preprocess method provides an efficient codec processor and transmission system for underwater images that are used for searches and transmitted via ultrasonic communications.