• Journal of Ship and Ocean Technology
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• 제5권3호
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• pp.27-35
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• 2001

In this research, hybrid method with case-based reasoning and rule-based reasoning is applied. Using case-based reasoning, design experts'experience and know-how are effectively represented in order to obtain a proper configuration of midship section in the initial ship design stage. Since there is not sufficient domain knowledge available to us, traditional case-adaptation algorithms cannot be applied to our problem, i.e., creating the configuration of midship section. Thus, new case-adaptation algorithms not requiring any domain knowledge are developed antral applied to our problem. Using the knowledge representation of DnV rules, rule-based reasoning can perform deductive inference in order to obtain the scantling of midship section efficiently. The results from the case-based reasoning and the rule-based reasoning are examined by comparing the results with various conventional methods. And the reasonability of our results is verified by comparing the results wish actual values from parent ship.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2005년도 춘계공동학술대회 발표논문
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• pp.157-163
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• 2005

Nowadays, the web service was based on composing the e-business and distributed computing environment. But existing workflow management systems have many problems with the interoperability between companies because they are made before most web services. For these problems, the workflow based composition language such as the Business Process Execute Language for Web Services (BPEL4WS or BPEL) appeared in expressing the web service composition. In this paper, we present an event based rule management system architecture that executes automatically the BPEL using the Event-Condition-Action (ECA) rules. The event based rule management system consists of the event manager, rule manager, and Jess. The Jess is the part of executing and deciding the condition.

• 제어로봇시스템학회논문지
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• 제11권2호
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• pp.127-136
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• 2005

In this paper, a new architecture and comprehensive design methodology of genetically optimized Rule-based Fuzzy Polynomial Neural Networks(gRFPNN) are introduced and a series of numeric experiments are carried out. The architecture of the resulting gRFPNN results from asynergistic usage of the hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks (PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the gRFPNN. The consequence part of the gRFPNN is designed using PNNs. At the premise part of the gRFPNN, FNN exploits fuzzy set based approach designed by using space partitioning in terms of individual variables and comes in two fuzzy inference forms: simplified and linear. As the consequence part of the gRFPNN, the development of the genetically optimized PNN dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the gRFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed gRFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• 한국지능시스템학회논문지
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• 제14권5호
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• pp.587-592
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• 2004

본 논문에서는 실시간으로 상수 및 변수의 병렬 매칭이 가능한 새로운 구조의 하드웨어 기반 룰-베이스 시스템 구조를 제안한다. 이 시스템은 context-aware computing 시스템에서 상황 인식을 위한 기법으로 적용될 수 있다. 제안한 구조는 기존의 하드웨어 기반의 구조가 가지는 룰의 표현 및 룰의 구성에서 발생하는 제약을 상당히 감소시킬 수 있다. 이를 위해 변형된 형태의 content addressable memory(CAM)와 crossbar switch network(CSN)가 사용되었다. 변형된 형태의 CAM으로 구성된 지식-베이스는 동적으로 데이터의 추가 및 삭제가 가능하다. 또한 CSN은 input buffer와 working memory(WM) 사이에 위치하여, 시스템 외부 및 내부에서 동적으로 생성되거나, 시스템의 설정에 의해 지정된 데이터들의 조합 및 pre-processing module(PPM)을 이용한 연산을 통하여 WM을 구성하는 데이터를 생성시킨다. 이 하드웨어 룰-베이스 시스템은 SystemC ver. 2.0을 이용하여 설계되었으며 시뮬레이션을 통하여 그 동작을 확인 및 검증하였다.

• International Journal of Control, Automation, and Systems
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• 제1권3호
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• pp.321-331
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• 2003

Experimental software datasets describing software projects in terms of their complexity and development time have been the subject of intensive modeling. A number of various modeling methodologies and modeling designs have been proposed including such approaches as neural networks, fuzzy, and fuzzy neural network models. In this study, we introduce the concept of the Rule-based fuzzy polynomial neural networks (RFPNN) as a hybrid modeling architecture and discuss its comprehensive design methodology. The development of the RFPNN dwells on the technologies of Computational Intelligence (CI), namely fuzzy sets, neural networks, and genetic algorithms. The architecture of the RFPNN results from a synergistic usage of RFNN and PNN. RFNN contribute to the formation of the premise part of the rule-based structure of the RFPNN. The consequence part of the RFPNN is designed using PNN. We discuss two kinds of RFPNN architectures and propose a comprehensive learning algorithm. In particular, it is shown that this network exhibits a dynamic structure. The experimental results include well-known software data such as the NASA dataset concerning software cost estimation and the one describing software modules of the Medical Imaging System (MIS).

• Journal of Ship and Ocean Technology
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• 제6권1호
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• pp.16-26
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• 2002

In this paper, a motion identification method using neural networks is applied to automatic ship berthing to overcome disturbance effects. Motion identification is used to estimate the effect of environmental disturbance. Two rule-based algorithms have been developed to over-come disturbance. The first rule based-algorithm was designed to overcome lateral disturbance when a ship's lateral speed is affected by it. The second rule-based algorithm was also designed to overcome longitudinal disturbance when a ship's angular velocity is changed by it. Finally, numerical simulations for automatic berthing are carried out, and the suggested control system is proved to be more practical under disturbance circumstances.

• 한국경영과학회지
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• 제30권2호
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• pp.185-199
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• 2005

With the growth of internet shopping malls, there is increasing interest in comparison shopping mall. However most comparison sites compare only book prices by collecting simple XML data and do not provide .the exact comparison Including precise shipping costs. Shipping costs vary depending on each customer's address, the delivery method, and the category of selected goods, so rule based system is required in order to calculate exact shipping costs. Therefore, we designed and implemented comparison shopping mall which compares not only book prices but also shipping costs using rule based inference. By adopting the extensible Rule Markup language (XRML) approach, we proposed the methodology of extracting delivery rules from Web pages of each shopping mall. The XRML approach can facilitate nearly automatic rule extraction from Web pages and consistency maintenance between Web pages and rule base. We developed a ConsiderD system which applies our rule acquisition methodology based on XRML. The objective of the ConsiderD system is to compare the exact total cost of books including the delivery cost over Amazon.com, BarnesandNoble.com, and Powells.com. With this prototype, we conducted an experiment to show the potential of automatic rule acquisition from Web pages and illustrate the effect of delivery cost.

• 한국통신학회논문지
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• 제41권12호
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• pp.1858-1860
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• 2016

논문에서는 YARA의 스캐닝 스레드 알고리즘을 개선하여 다수의 룰 파일 패턴 매칭을 수행할 수 있는 새로운 소프트웨어 구조를 제안한다. 제안하는 방식은 기존의 YARA에 비해 매칭을 위한 룰 파일의 메모리 적재 횟수를 감소시킨다. 따라서 제안된 구조를 적용할 경우 메모리 사용량은 룰 파일의 개수에 비례하여 증가하지만 패턴 매칭 수행에 따른 시간을 감소시킬 수 있다.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2003년도 추계학술대회 및 정기총회
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• pp.51-57
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• 2003

In operating distributed systems, proactive management is one of the major concerns for better quality of service and future capacity planning. In order to handle this management problem effectively, it is necessary to analyze performances of the distributed system and events generated by components in the system. This paper provides a rule-based event parsing engine for proactive management. Our event parsing engine uses object hooking-based and event-token approaches. The object hooking-based approach prepares new conditions and actions in Java classes and allows dynamically exchange them as hook objects in run time. The event-token approach allows the event parsing engine consider a proper sequence and relationship among events as an event token to trigger an action. We analyze the performance of our event parsing engine with two different implementations of rule structure; one is table-based and the other is tree-based.

• 한국산학기술학회논문지
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• 제16권1호
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• pp.735-743
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• 2015

서비스 지향 아키텍처(Service Oriented Architecture)는 엔터프라이즈 애플리케이션 개발 시 유연성을 보장하여, 비즈니스 변화에 최대한 민첩하게 대응하도록 지원한다. 그럼에도 불구하고 비즈니스와 제약조건을 하나의 서비스로 코딩하는 일반적 접근법은 비즈니스 룰의 변경을 위하여 전체 결합로직을 변경하는 등 많은 자원을 소모하게 된다. 본 논문에서는 이러한 문제점을 개선하기 위하여 서비스 시스템 개발에 관점 지향 기법(Aspect Oriented Approach)을 확장하여 적용한다. 관점 지향 기법의 기존 핵심관심(Core Concern), 횡단관심(Cross Cutting Concern)이외에 비즈니스 프로세스와 서비스에 포함된 비즈니스 룰을 룰관심(Rule Concern)이라는 새로운 관심사로 분리한다. 룰관심은 수준에 따라 프로세스 룰관심(PRA: Process Rule Aspect)과 서비스 룰관심(SRA: Service Rule Aspect)으로 구분된다. 시스템은 이러한 관심사의 분리를 통하여 핵심관심, 횡단관심 및 룰관심으로 각각 모듈화 되고 독립적으로 유지보수 되어 서비스 시스템의 적용성, 재사용성 및 유지보수성을 높일 수 있다.