• 한국전자통신학회논문지
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• 제6권6호
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• pp.849-854
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• 2011

시스템 이벤트들로부터 그 파급효과를 최소화하기 위해서는 실시간 조건에 기반한 규칙기반 전문가 시스템이 매우 효과적인데, 그 이벤트가 다양하고 부하조건이 매우 가변적이기 때문에 규칙 기반 전문가 시스템을 구축하기가 쉽지 않다. 따라서 본 연구에서는 CART 알고리즘 기반의 의사결정 트리 기법을 적용하여 상정사고 사례들로부터 규칙기반 전문가 시스템을 구축하는 방법론에 대해서 연구하고자 한다.

• 한국IT서비스학회지
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• 제9권3호
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• pp.123-144
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• 2010

As knowledge becomes a critical success factor of companies nowadays, lots of rule-based systems have been and are being developed to support their activities. Large number of rule-based systems serve as Web sites to advise, or recommend their customers. They usually use a backward chaining inference algorithm based on backtrack to implement those interactive Web-enabled rule-based systems. However, when the users like customers are using these systems interactively, it happens frequently where the users do not know some of the answers for the questions from the rule-based systems. We are going to design a backward chaining inference methodology considering unknown facts based on backtrack technique. Firstly, we review exact and inexact reasoning. After that, we develop a backward chaining inference algorithm for exact reasoning based on backtrack, and then, extend the algorithm so that it can consider unknown facts and reduce its search space. The algorithm speeded-up inference and decreased interaction time with users by eliminating unnecessary questions and answers. We expect that the Web-enabled rule-based systems implemented by our methodology would improve users' satisfaction and make companies' competitiveness.

• 반도체디스플레이기술학회지
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• 제17권1호
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• pp.6-11
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• 2018

With the development of the Internet of Things technology, a system that ensures the self-adaptability of an environment that includes various IoT devices is attracting public attention. The rules for determining behavior rules in existing self-adaptation systems are based on the assumption of changes in system members and environment. However, in the IoT environment, flexibility is required to determine the behavior rules of various types of IoT devices that change in real time. In this paper, we propose a rule configuration in a self-adaptive system using SWRL based on OWL ontology. The self-adaptive system using the OWL - SWRL rule configuration has two advantages. The first is based on OWL ontology, so we can define the characteristics and behavior of various types of IoT devices as an integrated concept. The second is to define the concept of a rule as a specific language type, and to add, modify and delete a rule at any time as needed. Through the rule configuration in the adaptive system, we have shown that the rule defined in SWRL can provide flexibility and deeper concept expression function to adaptability to IoT environment.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2009년도 춘계학술대회 논문집
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• pp.1057-1058
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• 2009

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제11권3호
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• pp.246-256
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• 2005

규칙 기반 패러다임은 복잡한 프로세스를 처리할 수 있는 정형성과 융통성을 제공하기 때문에 여러 프로세스 중심 소프트웨어 공학 환경에 도입되어 왔다 그러나, 기존의 규칙 기반 패러다임을 채택한 시스템들의 경우 프로세스 모델을 작성하거나 이해하기 어렵고 프로세스 모델링 언어가 확장 또는 개선될 때마다 추론 엔진을 수정하거나 최악의 경우에는 새로 개발하여야 한다. 본 논문에서는 빈번히 발생하는 프로세스 변경에 유동적으로 대처할 수 있으며 프로세스 모델을 규칙기반 언어의 사실로 직관적으로 맵핑함으로써 프로세스의 병렬성을 효과적으로 제어할 수 있다는 규칙 기반 패러다임의 장점을 살리면서 기존 규칙 기반 PSEE의 단점인 사용의 용이성과 추른 엔진의 안정성 문제를 해결한 PRAiSE 시스템을 기술한다. PRAiSE에서는 RAiSE라는 그래픽 프로세스 모델링 언어를 제공하며 작성된 프로세스 모델은 규칙 기반 전문가 시스템 도구인 CLiPS로 구현한 프로세스 엔진에 의해 해석되고 실행된다.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2004년도 춘계학술대회
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• pp.25-38
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• 2004

Association rule mining searches for interesting relationships among items in a given database. Association rules are frequently used by retail stores to assist in marketing, advertising, floor placement, and inventory control. There are three primary quality measures for association rule, support and confidence and lift. In this paper we present the relation between the measure of association based on chi square statistic and the criteria of association rule for nominal database and propose the objective criteria for association.

• 한국정보처리학회논문지
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• 제4권9호
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• pp.2299-2308
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• 1997

대부분의 기계학습 방법들은 특정한 방법을 중심으로 연구되어 왔다. 하지만 두 가지 이상의 기계학습방법을 효과적으로 통합할 수 있는 방법에 대한 요구가 증가하며, 이에 따라 본 논문은 귀납법칙 (rule induction) 방법과 개체위주 학습방법 (instance-based learning)을 통합하는 시스템의 개발을 제시한다. 귀납법칙 단계에서는 엔트로피 함수의 일종인 Hellinger 변량을 사용하여 귀납법칙을 자동 생성하는 방법을 보이고, 개체위주 학습방법에서는 기존의 알고리즘의 단점을 보완한 새로운 개체위주 학습방법을 제시한다. 개발된 시스템은 여러 종류의 데이터에 의해 실험되었으며 다른 기계학습 방법과 비교되었다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.116-132
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• 2022

Automated medical claims processing and billing is a popular application domain of information technology. Managing medical related data is a tedious job for healthcare professionals, which distracts them from their main job of healthcare. The technology used in data management has a sound impact on the quality of healthcare data. Most of Information Technology (IT) organizations use conventional software development technology for the implementation of healthcare systems. The objective of this experimental study is to devise a mechanism for use of rule-based expert systems in medical related edits and compare it with the conventional software development technology. A sample of 100 medical edits is selected as a dataset to be tested for implementation using both technologies. Besides empirical analysis, paired t-test is also used to validate the statistical significance of the difference between the two techniques. The conventional software development technology took 254.5 working hours, while rule-based technology took 81 hours to process these edits. Rule-based technology outperformed the conventional systems by increasing the confidence value to 95% and reliability measure to 0.462 (which is < 0.5) which is three times more efficient than conventional software development technology.

• 한국CDE학회논문집
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• 제22권1호
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• pp.1-9
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• 2017

This research develops dispatching rule for a wafer FABs with dedication constraints. Dedication, mostly considered in a photolithography step, is a feature in a modern FABs in order to increase the yield of machines and achieve the advance of manufacturing technology. However, the dedication has the critical problem because it causes dedication load of machines to unbalance. In this paper, we proposes the dedication load based dispatching rule for load balancing in order to resolve the problem. The objective of this paper is to balance dedication load of photo machines in wafer FABs with dedication constraint. Simulation experiments show that the proposed rule improves the performance of wafer FABs as well as load balance for dedication machines compared to open-loop control based conventional dispatching rule.

• 한국경영과학회지
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• 제25권4호
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• pp.81-95
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• 2000

A knowledge-based system with fuzzy production rules is a representation of static knowledge of an expert. On the other hand, a real system such as the stock market is dynamic in nature. Therefore we need a strategy to reflect the dynamic nature of real system when we make inferences with a knowledge-based system. This paper proposes a strategy of dynamic inferencing for a knowledge-based system with fuzzy production rules. The strategy suggested in this paper applies weights of attributes of conditions of a rule in the knowledge-base. A degree of match(DM) between actual input information and a condition of a rule is represented by a value [0,1]. Weights of relative importance of attributes in a rule are obtained by AHP(Analytic Hierarcy Process) method. Then these weights are applied as exponents for the DM, and the DMs in a rule are combined, with MIN operator, into a single DM for the rule. In this way, overall DM for a rule changes depending on the importance of attributes of the rule. As a result, the dynamic nature of a real system can be incorporated in an inference with fuzzy production rules.