• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.430-435
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• 1992

Hazard identification is one of the most important task in process design and operation. This work has focused on the development of a knowledge-based expert system for HAZOP (Hazard and Operability) studies which are regarded as one of the most systematic and logical qualitative hazard identification methodologies but which require a multidisciplinary team and demand much time-consuming, repetitious work. The developed system enables design engineers to implement existing checklists and past experiences for safe design. It will increase efficiency of hazard identification and be suitable for educational purposes. This system has a frame-based knowledge structure for equipment failures/process material properties and rule networks for consequence reasoning which uses both forward and backward chaining. To include wide process knowledge, it is open-ended and modular for future expansion. An application to LPG storage and fractionation system shows the efficiency and reliability of the developed system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.4
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• pp.353-359
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• 2005

In this research, we propose a Unified Fuzzy rule-based knowledge Inference Systems (UFIS) to help the expert in cosmetic brand detection. Users' preferred cosmetic product detection is very important in the level of CRM. To this purpose, many corporations trying to develop an efficient data mining tool. In this study, we develop a prototype fuzzy rule detection and inference system. The framework used in this development is mainly based on two different mechanisms such as fuzzy rule extraction and RDB (Relational DB)-based fuzzy rule inference. First, fuzzy clustering and fuzzy rule extraction deal with the presence of the knowledge in data base and its value is presented with a value between 0 -1. Second, RDB and SQL (Structured Query Language)-based fuzzy rule inference mechanism provide more flexibility in knowledge management than conventional non-fuzzy value-based KMS (Knowledge Management Systems).

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.121-130
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• 1999

The objective of this paper is to apply Extended AND-OR Graph (EAOG)-related techniques to extract knowledge from a specific problem-domain and perform analysis in complicated decision making area. Expert systems use expertise about a specific domain as their primary source of solving problems belonging to that domain. However, such expertise is complicated as well as uncertain, because most knowledge is expressed in causal relationships between concepts or variables. Therefore, if expert systems can be used effectively to provide more intelligent support for decision making in complicated specific problems, it should be equipped with real-time inference mechanism. We develop two kinds of EAOG-driven inference mechanisms(1) EAOG-based forward chaining and (2) EAOG-based backward chaining. and The EAOG method processes the following three characteristics. 1. Real-time inference : The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matrix computation. 2. Matrix operation : All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient. 3. Bi-directional inference : Traditional inference method of expert systems is based on either forward chaining or backward chaining which is mutually exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.79-90
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• 1995

The material handling equipment selection, that is a key task in the material handling system design, is a complex, difficult task, and requires a massive technical knowledge and systematic analysis. It is invaluable to justify the selected equipment model by the performance evaluation before its actual implementation. This paper presents an intelligent knowledge-based expert system called "IMESE" created by authors, for the selection and evaluation of material handling equipment model suitable for movement and storage of materials in a manufacturing facility. The IMESE is consisted of four modules: a knowledge base to select an appropriate equipment type, a multiple criteria decision making procedure to choose the most favorable commercial model of the selected equipment type, a database to store the list of commercial models of equipment types with their specifications, and simulators to evaluate the performance of the equipment model. The whole process of IMESE is executed under VP-Expert expert system environment.vironment.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.199-202
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• 2000

In this paper, we developed an expert system that helped a machine-tool designer to select a moderate servomotor of the feed drive unit of a machine tool. With the specification of the drive unit, it searches for the set of servo-motors that have enough torque and power to satisfy the driving condition which the designer defines from the database. me database also contains knowledge and rules, which describe the design process and calculate design parameters of a feed drive. The knowledge-based design support module shows every steps of inference and reason for the solution that it provides.

• Proceedings of the Korea Concrete Institute Conference
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• 1993.10a
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• pp.71-78
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• 1993

The R/C structures is very popular because of its low construction cost and its semi-permanent life. But in Korea, unfortunately there are few exprets in this field, and the repair methods and selection of material for R/C structures are determined by their subjective personal opinions. Therefore systematic study of this field is ulgently required. For attainning this purpose, in this study the related documents and knowledge or experience from human experts were collected. Based on the collected information cracks are classified into 25 patterns and repair related-knowledge base, which will be formulated and encoded into the domain knowledge, is built. And then an expert system, that can suggest the repair methods in the same way the human experts would, is developed. The results using the developed expert system are compared to the real field practices and they are satisfactory.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.185-195
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• 1997

In this paper, research and applications of a knowledge-base system in scheduling are review. The method is based on the problem-solving techniques developed in artificial intelligent. The object of this paper is to enable the re-time rescheduling under dynamic environments. Developed to KBS(Knowledge-Based Scheduling) system in this paper, will based on expert system, and applicate to requirement of users effectively.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.10a
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• pp.461-467
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• 1998

Although many methods of knowledge acquisition has been developed in the expert systems field, such a need for causal knowledge acquisition has not been stressed relatively. In this respect, this paper is aimed at suggesting a causal knowledge acquisition process, and then investigate the causal knowledge-based inference process. A vehicle for causal knowledge acquisition is FCM (Fuzzy Cognitive Map), a fuzzy signed digraph with causal relationships between concept variables found in a specific application domain. Although FCM has a plenty of generic properties for causal knowledge acquisition, it needs some theoretical improvement for acquiring a more refined causal knowledge. In this sense, we refine fuzzy implications of FCM by proposing fuzzy implications of FCM by proposing fuzzy causal relationship and fuzzy partially causal relationship. To test the validity of our proposed approcach, we prototyped a causal knowledge-driven inference engine named CAKES and then experime ted with some illustrative examples.

• Journal of the Korean Dietetic Association
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• v.7 no.3
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• pp.295-306
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• 2001

The purpose of the study was to develop an internet nutritional counseling program using an expert system to assist obese people to lose weight through behavior modification. The internet counseling program for weight loss was developed by the accumulation of knowledge dealing with eating habits and exercising behaviors in expert system tool, Knowledge Engineering Agent (KEA) by a dietitian without any help of computer expert. To accumulate knowledge into KEA, survey was performed in 150 obese people, dietitians reviewed and consulted each survey case, and the consulted contents were learned and accumulated into KEA. Survey questionnaire was the same as that of the internet consulting program, and it included general characteristics, dietary habits, lifestyle, and exercise patterns related to obesity. Also, the dietitian selected proper factors inferred from the survey questionnaire of each case, and added the conclusions for them. Conclusions were made for helping clients to correct bad eating behaviors and accumulate good behaviors to lose weight. Counseling was divided into two parts; a two-week part and a daily part. Two-week counseling was performed based on 4 step questionnaires, and daily counseling was done for daily food consumption and physical activity. When clients answered survey questionnaires in a counseling internet program, the recommendations on how to eat, to exercise and to deal with stress in a real time for each case, was given. In conclusion, a counseling internet program for weight reduction can be used to give advices how to deal with obesity in a man-to-man way in a real time using KEA where nutritional knowledge based on behavior modification for weight loss was accumulated.

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.190-192
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• 1997

In this paper we developed an object-based expert system for electric power system fault diagnosis. The object corresponds to a hardware or event in real world and they are independent each other. The expert system is designed to estimate the fault sections and identify the false operation, nonoperation of protective devices. The expert system was developed using C++ language in pentium PC. We applied the expert system in various sample systems and showed that making up a knowledge base is easier and diagnosis was done in a approximately real time.