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A METHOD OF IMAGE DATA RETRIEVAL BASED ON SELF-ORGANIZING MAPS
Mal-Rey Lee,Jong-Chul Oh 한국전산응용수학회 2002 Journal of applied mathematics & informatics Vol.9 No.2
Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations ( similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.
A METHOD OF IMAGE DATA RETRIEVAL BASED ON SELF-ORGANIZING MAPS
Lee, Mal-Rey,Oh, Jong-Chul 한국전산응용수학회 2002 The Korean journal of computational & applied math Vol.9 No.2
Feature-based similarity retrieval become an important research issue in image database systems. The features of image data are useful to discrimination of images. In this paper, we propose the highspeed k-Nearest Neighbor search algorithm based on Self-Organizing Maps. Self-Organizing Maps (SOM) provides a mapping from high dimensional feature vectors onto a two-dimensional space. The mapping preserves the topology of the feature vectors. The map is called topological feature map. A topological feature map preserves the mutual relations (similarity) in feature spaces of input data. and clusters mutually similar feature vectors in a neighboring nodes. Each node of the topological feature map holds a node vector and similar images that is closest to each node vector. In topological feature map, there are empty nodes in which no image is classified. We experiment on the performance of our algorithm using color feature vectors extracted from images. Promising results have been obtained in experiments.
이말례(Mal Rey Lee),황수철(Su Cheol Hwang),김기태(Ki Tae Kim) 한국정보과학회 1994 정보과학회논문지 Vol.21 No.9
퍼지 논리의 응용 영역중의 가장 활발한 영역이 퍼지 제어기이다. 퍼지 제어기의 대부분은 전문가의 정량적인 지식과 실험적 기술 또는 경험이 있는 오퍼레이터로 부터 얻어진 IF-THEN 형태의 규칙으로 퍼지 모델을 구성한다. 기존의 자기동조 방법에서의 충분한 생성능력과 획득한 지식을 표현하는 능력이 부족하다. 따라서 본 논문에서는 유전 알고리즘에 의해 퍼지 IF-THEN 규칙을 자기 동조하는 방법을 제안한다. 제안한 방법은 기존의 하강 방법보다 자기동조 속도가 빠르고, 획득한 지식을 보다 효율적으로 표현할 수 있는 능력이 있다. One of the most active areas in the application of fuzzy logic is about fuzzy controllers. Most of these controllers are constituted of a fuzzy model described in the IF-THEN type rules derived from the qualitative knowledge and the experimental knowhow of experts or experienced operators. Conventional methods don't have a sufficient generalization capability and an expressing capability of the acquired knowledge. So, in this paper we propose a self-tuning method of fuzzy IF-THEN rules by a genetic algorithm. The proposed method has high speed self-tuning capability than a conventional descent method. And it has an expressing capability of acquired knowledge.
INFORMATION SEARCH BASED ON CONCEPT GRAPH IN WEB
Lee, Mal-Rey,Kim, Sang-Geun 한국전산응용수학회 2002 Journal of applied mathematics & informatics Vol.10 No.1
This paper introduces a search method based on conceptual graph. A hyperlink information is essential to construct conceptual graph in web. The information is very useful as it provides summary and further linkage to construct conceptual graph that has been provided by human. It also has a property which shows review, relation, hierarchy, generality, and visibility. Using this property, we extracted the keywords of web documents and made up of the conceptual graph among the keywords sampled from web pages. This paper extracts the keywords of web pages using anchor text one out of hyperlink information and makes hyperlink of web pages abstract as the link relation between keywords of each web page. 1 suggest this useful search method providing querying word extension or domain knowledge by conceptual graph of keywords. Domain knowledge was conceptualized knowledged as the conceptual graph. Then it is not listing web documents which is the defect of previous search system. And it gives the index of concept associating with querying word.
EXPERT SYSTEM FOR A NUCLEAR POWER PLANT ACCIDENT DIAGNOSIS USING A FUZZY INFERENCE METHOD
Lee, Mal-Rey,Oh, Jong-Chul 한국전산응용수학회 2001 The Korean journal of computational & applied math Vol.8 No.2
The huge and complicated plants such as nuclear power stations are likely to cause the operators to make mistakes due to a variety of inexplicable reasons and symptoms in case of emergency. That’s why the prevention system assisting the operators is being developed for. First of all. I suggest an improved fuzzy diagnosis. Secondly, I want to demonstrate that a classification system of nuclear plant’s accident investigating the causes of accidents foresees possible problems, and maintains the reliability of the diagnostic reports in spite of improper working in part. In the event of emergency in a nuclear plant, a lot of operational steps enable the operators to find out what caused the problems based on an emergent operating plan. Our system is able to classify their types within twenty to thirty seconds. As so, we expect the system to put down the accidents right after the rapid detection of the damage control-method concerned. AMS Mathematics subject Classification : 93C42
이말례(Mal Rey Lee),조상엽(Sang Yeop Cho),김기태(Ki Tae Kim) 한국정보과학회 1993 한국정보과학회 학술발표논문집 Vol.20 No.1
이 논문에서는 유전자 알고리즘을 사용하는 퍼지 추폴ㄴ 규칙의 학습 방법을 제안한다. 유전자 알고리즘을 사용하면 전문가로부터 획득한 입출력 자료로부터 입출력 자료간의 관계를 적절히 표현할 수 있는 추론 규칙을 자동적으로 얻을 수 있다. 학습을 위한 매개변수로 사용되는 추론 규칙의 전제부에 있는 소속함수와 결론부에 있는 실수는 유전자 알고리즘에 의해서 조정된다. 유전자 알고리즘을 이용한 학습 속도와 추론 규칙 생성 능력은 신경망의 역전과 알고리즘 보다 효율적이다.