• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.135-135
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• 1991

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.721-723
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• 2005

패턴 분류에 많이 사용되는 MBR(Memory Based Reasoning) 기법은 메모리에 저장된 학습패턴과 테스트 패턴간의 거리를 계산하여 가장 가까운 학습패턴의 클래스로 분류하기 때문에 테스트 패턴을 분류하는 기준을 설명할 수 없다는 문제점을 가지고 있다. 본 논문에서는 RPA(Recursive Partition Averaging) 기법을 이용하여 분류 기준을 설명할 수 있는 IF-THIN 형태의 규칙을 생성하고 생성된 규칙의 일반화 성능을 향상시키기 위하여 불필요한 조건을 제거하는 규칙 pruning 알고리즘과 생성되는 규칙의 개수를 줄일 수 있는 점진적 규칙 추출 알고리즘을 제안한다.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.273-278
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• 1998

Belief network(or Bayesian network) based on Bayes' rule in probabilistic theory can be applied to the reasoning of diagnostic systems. This paper describes the basic theory of concept and feasibility of using the network for diagnosis of nuclear power plants. An example shows that the probabilities of root causes of a failure are calculated from the measured or believed evidences.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.31-40
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• 2000

A robust scheme of locating and counting the number of vehicles m urban traffic scenes, a core component of vision-based traffic monitoring systems, is presented The method is based on the evidential reasoning, where vehicle evidences m the background subtraction Image are obtained by a new locally optimum thresholding, and the evidences are merged by three heuristic rules using the geometric constraints The locally optimum thresholding guarantees the separation of bright and dark evidences of vehicles even when the vehicles are overlapped or when the vehicles have similar color to the background Experimental results on diverse traffic scenes show that the detection performance is very robust to the operating conditions such as the camera location and the weather The method may be applied even when vehicle movement is not observed since a static Image IS processed without the use of frame difference.

• The Journal of Information Technology
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• v.7 no.3
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• pp.127-137
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• 2004

A Project planning is one of the most important processes that determines success and failure of a project. Scope management for a project planning is also essential job in system integration project. However project planning is very difficult because lots of factors and their relationships should be considered. Therefore project planning of system integration project has been done by project manager's own knowledge and experience. It is necessary to develop an algorithm of WBS(Work Breakdown Structure) identification & document selection along to project's specificity in project management system using AI technique. This study presents a methodology to cope with the limitations of the existing studies that have uniformly been customizing the methodology by only project complexity. We propose PPSM(Project planning support module) based on determination rules regarding route maps and document levels, and CBR(Case-Based Reasoning) for WBS identification.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.452-456
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• 2011

Context-awareness system can provide an optimized services to users. Analyzing physical and complex circumstance elements which give direct or indirect influence to users can tell what users want. However, there are various situation informations around users and it requires high level technology to extract the service what users really want among those informations. The circumstance of the user can be changed from moment to moment, even the service what users want also can be changed in every minutes. Recently the researches to provide the service which a user demands has been progressed actively. Web based filtering method which reaches commercialization is a one of good examples. This method extracts necessary data according to users' demands from the documents on the Web or multimedia informations. However, there is a limit to use it to provide Context-awareness service because it extracts static data, not dynamic data. There is also other researches with a rule based filtering method in progress to filter situation information but this method doesn't have mechanism for dynamic data as well. We would like to solve these problems by providing a dynamic situation information filtering mechanism applying an weighted value about each property of objects and also applying Web based dynamic categories in this paper when unnecessary data should be filtered.

• Journal of Korean Society for Quality Management
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• v.20 no.1
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• pp.147-157
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• 1992

This article describes a prototype expert system for yarn spinning process planning in textile industry. This expert system is intended as a consultant to give the technicians interactive assistance for the appropriate process planning in accordance with used materials, required count, and other factors affected yarn spinning by means of many types of machine. Also, this system has the other function that can be compared the standard values with the measured ones for quality characteristics control. VP-EXPERT-a rule-based microcomputer expert system development tool-provides the expert system components for this development. The details of knowledge organization, rule representation, inference reasoning process, and performance of this expert system are demonstrated with the practical yarn spinning operations.

• Journal of Ocean Engineering and Technology
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• v.17 no.1
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• pp.67-71
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• 2003

This paper presents the use of an evert system to automate process planning of block assembly, a task that is usually completed manually. In order to determine the sequence of assembly operation, a search method guided by rules, such as merging of related operations, grouping of similar operations, and precedence rules based on know-hows and geometrical reasoning, is used. In this paper, the expert system developed is explained in detail regarding a global database, control strategies, and rule bases. For verification purposes, the evert system has been applied to simple examples. Since the rule bases are isolated from the inference engine in the developed system, it is easy to add more rules in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.382-385
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• 2006

오늘날의 네트워크 환경은 다기능, 멀티 벤더(Multi-Vendor)의 분산 환경으로 장비 및 프로토콜의 다양성, 네트워크 구조의 복잡성, 지역적 분산 등 광대하고 복잡한 네트워크로 구성되어 있다. 따라서 기존의 Vendor NMS를 사용한 NMS가 일부 이루어지고 있으나 복잡한 네트워크 구성에 부합하는 신속한 장애 파악이 어려운 실정이다. 본 논문에서는 복잡하고 다양한 멀티 네트워크 환경에서 이벤트 상관관계 장애관리에 구현기법을 기술하고자 한다.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.15-27
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• 2000

The paper proposes a hybrid fire fighting control intelligent system(H-FFIS) using rules and cases to detect fire in Integrated Platform Management System. By far most conventional systems have been based on rule-based system in which expert knowledges are expressed with production rules. It is hard to express the knowledges to detect fire with production rules only. The knowledges of fire detection are often based on previously encountered situations of fires. For improvement of system capability renewing and adding of rules is needed in an already build-up system and such adding and renewing procedures could hinder users from fluent utilization of the system. We design and implement H-FFIS. Compared with rule-based FFIS(Fire Fighting control Intelligent System), H-FFIS extended with case-based reasoning shows that the system proposed here can lead to an improvement in fire detection rate.