• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.486-495
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• 2001

This paper describes an implementation of the interval based expert system for syndrome differential diagnosis of Oriental Traditional Medicine (OTM). An approximate reasoning model using fuzzy logic for syndrome differential diagnosis is proposed. Based on this model, we implemented the system for diagnosing Eight rule diagnosis, organ diagnosis and then final differential syndrome of OTM. After carrying out inference process, the system will provide patient\`s syndromes differentiation diagnosis in the intervals and will give the explanation, which helps the user to understand the obtained conclusions.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.594-598
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• 2006

Many institutes and organizations carrying out the national R&D projects have and use the expert pool database at each need. But there is lack of human resources information about expert in science and technology part for many policy planning and committee activity, also most of the expert pools are scattered on several database systems. So it is necessary to manage systematically the human resources informations about scientific expert. As the committeeman assignment and committee findings management are conducted by the off-line method, there are wastes of time and labor in committeeman assignment process and committee history management. Therefore we need to provide an effective and automatic process for committeeman assignment and management. In this paper, we construct a database for expert pool who can be used in committee activity or policy planning, and implement a system that services committee management and committeeman assignment process. The human information retrieval service of this system is based on the KRISTAL-2002, an information retrieval and management system developed by KISTI.

• Journal of Information Management
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• v.36 no.4
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• pp.199-215
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• 2005

Experts participating in the knowledge expert network externalize their implicit knowledge by providing information or writing reports. Almost all the members of the network share externalized knowledge and the network facilitate the dissemination and diffusion of knowledge. Individuals reproduce another implicit knowledge by internalizing shared knowledge through the network and re-created knowledge is externalized, establishing knowledge circulation. In this paper, we analyze the expert groups of the Global Network of Korean Scientists & Engineers(KOSEN, www.kosen21.org), the Korea's No. 1 science and engineering knowledge expert community, with the application of the theory of policy network proposed by Marsh & Rhodes. According to the principal standards of policy network classification such as the number of participants, interaction among participants, consistency, distribution of resources and dependency, we categorize the KOSEN expert groups as closed policy network and opened issue network, and divide closed policy network into core community and periphery community.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.307-316
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• 2011

The majority of maritime accidents happened by human factor. For that reason, navigation experts want to an intelligent support system for navigation safety, without officer involvement. The expert system which is one of artificial intelligence skills for navigation support is an important tool that a machine can substitute for an expert through the design of a knowledge base and inference engine using the experience or knowledge of an expert. Further, in the real world, a complex situation requires synthetic estimation with the input of experts in various fields for the correct estimation of the situation, not any one expert. In particular, synthetic estimation is more important for navigation situations than in other cases, because of diverse potential threats. This paper presents the method of knowledge fusion pertaining to navigation safety knowledge from various expert systems, using a blackboard system. Then we will show the validity of the method via a design and implementation of test system effort.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.2
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• pp.323-338
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• 1994

This paper outlines a framework for performing intelligent sensor validation for a diagnostic expert system while reasoning under uncertainty. The emphasis is on the algorithmic preprocess technique. A companion paper focusses on heuristic post-processing. Sensor validation plays a vital role in the ability of the overall system to correctly detemine the state of a plant monitored by imperfect sensors. Especially, several theoretical developments were made in understanding uncertain sensory data in statistical aspect. Uncertain information in sensory values is represented through probability assignments on three discrete states, "high", "normal", and "low", and additional sensor confidence measures in Algorithmic Sv.Upper and lower warning limits are generated from the historical learning sets, which represents the borderlines for heat rate degradation generated in the Algorithmic SV initiates a historic data base for better reference in future use. All the information generated in the Algorithmic SV initiate a session to differentiate the sensor fault from the process fault and to make an inference on the system performance. This framework for a diagnostic expert system with sensor validation and reasonig under uncertainty applies in HEATXPRT$^{TM}$, a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.49-63
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• 2003

This paper proposes and implements a tool for the development of efficient and reliable expert system. In the expert system the inference is executed, based on the knowledges stored in the knowledge base of specific domain. To acquire the reliable results of inference, the expert system requires the facilities which can access the various kinds of knowledge and maintain the consistency and accuracy of knowledge. In this context this paper implemented the knowledge management system which maintains the consistency and accuracy of knowledge, adding selectively the knowledges without error to the knowledge base by verifying their error before the knowledges are added to the knowledge base. At the same time this paper made the expert system call and use the procedural knowledge and the declarative knowledge in the data base so that it might use the various kinds of knowledge in the process of inference.

• Journal of Intelligence and Information Systems
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• v.1 no.2
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• pp.17-32
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• 1995

본 논문에서는 추론엔진 (inference engine)내에 퍼지정보 검색부(Fuzzy Information Retrieval part)를 갖는 교통신도 제어 전문가 시스템을 제안한다. 제안하는시스템은 다양하고 복잡한 도로 상화을 고려하여 그에 따른 적절한 주기를 각 도로별로 할당함으로써 원활한 교통 흐름을 제어한다. 추론엔진내의 퍼지정보 검색부는 퍼지 삼각 논리곱을 이용하여 도로의 상황을 분석한 후 각 도로에 맞는 가장 적절한 신호주기를 생성한다.

• KIISE Transactions on Computing Practices
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• v.23 no.1
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• pp.1-12
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• 2017

Preventive maintenance is required for best performance of facilities in large scale industry. Ultimately, the efficiency of production is maximized by preventing the failure of facilities in advance. Typically, regular maintenance is conducted manually; however, it is hard to prevent repeated failures. Also, since measures to prevent failure depend on proactive problem-solving by the facility expert, they have limitations when the expert is absent or diagnosis error is made by an unskilled expert. Alarm system is used to aid manual facility diagnosis and early detection. However, it is not efficient in practice, since it is designed to simply collect information and is activated even with small problems. In this study, we designed and developed an automated preventive maintenance system based on expert's experience in detecting failure, determining the cause, and predicting future system failure. We also discussed the system structure designed to reuse the expert's knowledge and its applications.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2755-2762
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• 1997

Open Network Management Systems (NMS) are not sufficient to use in a large and complex computer network environment because many-year experiences and skills are requeired for using NMS. And also, customizing NMS means a difficult programming with API(Application programming Interface) supplied by NMs. The more intelligent NMS you want, the more difficult programming you must do. In this paper, we proposed an intelligent network management system suign a structure of multiple and distributed expert systems, so as to represent expertises and knowledges of network managers into rule format, maintain the knowledgesstructurally and perform the network managmenet intelligently. expert system for amanaging computer network should understand the management protocol, analyze messages from agents, take a proper action, and report the situations by pre-defined network operation principle and strategy. A multiple expert sytem is composed of monitor expert module, fault expert module and manager expert module which are controlled by enconded knowledges.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.