• International Journal of Safety
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• v.4 no.2
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• pp.12-17
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• 2005

This paper aims at the development of an knowledge base for an electrical fire cause diagnosis system using the entity relation database. The relation database which provides a very simple but powerful way of representing data is widely used. The system focused on database construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. In order to store and access to the information concerned with electrical fires, the key index items which identify electrical fires uniquely are derived out. The knowledge base consists of a case base which contains information from the past fires and a rule base with rules from expertise. To implement the knowledge base, Access 2000, one of DB development tools under windows environment and Visual Basic 6.0 are used as a DB building tool. For the reasoning technique, a mixed reasoning approach of a case based inference and a rule based inference has been adopted. Knowledge-based reasoning could present the cause of a newly occurred fire to be diagnosed by searching the knowledge base for reasonable matching. The knowledge-based database has not only searching functions with multiple attributes by using the collected various information(such as fire evidence, structure, and weather of a fire scene), but also more improved diagnosis functions which can be easily wed for the electrical fire cause diagnosis system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.588-592
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• 1996

In this paper, we have constructed an expert system for semiconductor chip encapsulation which combines a knowledge-based system with CAE software. The knowledge-base module includes heuristic and pre-analysis knowledge for evaluation and redesign. Evaluation of the initial design and generation of redesign recommendations can be developed from the rules as applied to a given chip Package. The CAE programs can be used for simulating the filling and packing stage of encapsulation process. The expert system is a new tool which enables package design or process conditions with high yields and high productivity.

• 제어로봇시스템학회:학술대회논문집
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• 1986.10a
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• pp.431-436
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• 1986

The design and manufacture of injection molded polymeic parts with desired mechanical properties is a costly process dominated by empiricism, including the modification of actual tooling. This paper presents an interactive computer-based design system for injection molded plastic parts. This knowledge-based synthesis system provides a rational design strategy for injection molding and molded parts. It synergistically combines a rule-based expert system for hurestic knowledge with analytical process simulation programs. The theremomechanical properties of a molded part such as the effect of molecular orientation and weldline strength are predicted by the analysis programs; while the expert system interprets the analytical results from the process simulation, evaluates the design, and generates recommendations for optimal design alternatives. The heuristic knowledge of injection molding is formalized as production rules of the expert consultation system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.137-140
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• 1996

In order to solve the specific problems in system, the implementing of knowledge base suitable to the system architecture has to be expressed and leads to the resoning of the new facts. Not only the simple knowledge based on the bivalent logic but also the representation and acqusition of knowledge related to vague and imprecise linguistic variable is necessary to the knowledge in the real world,i.e the knowledge of which facts and rules are composed. In this point of view, this survey implements the inference and retrieval of the fuzzy linguistic variables so that it can process the ambiguous information which appears the imprecision of the linguistic boundary.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.451-456
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• 1989

New image coding system for facial images called 'Knowledge-based image coding' is described, in which input image is analyzed and output image is synthesized using analysis results. Analysis and synthesis method of facial expressions are presented. Synthesis rules are determined on the basis of facial muscles and are also used in analysis process to produce a faithful reconstruction of the original image. A number of examples are shown.

• Journal of Internet Computing and Services
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• v.5 no.4
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• pp.115-124
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• 2004

This paper presents a weighted fuzzy backward reasoning algorithm for rule-based systems based on weighted fuzzy Petri nets. The fuzzy production rules in the knowledge base of a rule-based system are modeled by weighted fuzzy Petri nets, where the truth values of the propositions appearing in the fuzzy production rules and the certainty factors of the rules are represented by fuzzy numbers. Furthermore, the weights of the propositions appearing in the rules are also represented by fuzzy numbers. The proposed weighted fuzzy backward reasoning generates the backward reasoning path from the goal node to the initial nodes and then evaluates the certainty factor of the goal node. The algorithm we proposed can allow the rule-based systems to perform weighted fuzzy backward reasoning in more flexible and human-like manner.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.49-52
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• 2003

In this research, we propose a mechanism to develop an inference engine and expert systems based on relational database and SQL (structured query language). Generally, former researchers had tried to develop an expert systems based on text-oriented knowledge base and backward/forward (chaining) inference engine. In these researches, however, the speed of inference was remained as a tackling point in the development of agile expert systems. Especially, the forward inference needs more times than backward inference. In addition, the size of knowledge base, complicate knowledge expression method, expansibility of knowledge base, and hierarchies among rules are the critical limitations to develop an expert systems. To overcome the limitations in speed of inference and expansibility of knowledge base, we proposed a relational database-oriented knowledge base and forward inference engine. Therefore, our proposed mechanism could manipulate the huge size of knowledge base efficiently, and inference with the large scaled knowledge base in a short time. To this purpose, we designed and developed an SQL-based forward inference engine using relational database. In the implementation process, we also developed a prototype expert system and presented a real-world validation data set collected from medical diagnosis field.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.8
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• pp.21-29
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• 2003

This paper describes a research work on the development of computer-aided design system for deep drawing & ironing of a high pressure vessel. An approach to the system is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, handbook, experimental results and empirical knowledge of field experts. An attempt is made to link programs incorporating a number of expert design rules with the process variables obtained by commercial FEM software, DEFORM and ANSYS, to form a useful package. It is composed of five main modules, which are calculation of product thickness, input, production feasibility check, process planning, and autofrettage process modules and two submodules, which are folding check and process variable verification submodules. Programs for the system have been written in AutoLISP on the AutoCAD 2000 using personal computer. The developed system makes it possible to design and manufacture large high pressure vessel requiring D.D.I. process more efficiently.

• Journal of Ship and Ocean Technology
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• v.5 no.3
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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.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.360-363
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• 1993

Fuzzy Logic Control immitating human decision making process is a novel control strategy based on expert's experience and knowledge and many process designers are developing its applications. But it is difficult to obtain a set of rules from human operator. And there is a limitation on adjusting to environmental changes. In this paper, we proposed adaptive fuzzy algorithm to overcome these difficulties using weights added to the rules. To verify the validity of this control strategy, we have implemented this algorithm for a DC servo motor with PD-type fuzzy controller.