• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.1
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• pp.159-177
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• 1995

The objective of this paper is to propose a knowledge-based fuzzy post adjustment so that unstructured problems can be solved more realistically by expert systems. Major part of this mechanism forcuses on fuzzily assessing the influence of various external factors and accordingly improving the solutions of unstructured problem being concerned. For this purpose, three kinds of knowledge are used : user knowledge, expert knowledge, and machine knowledge. User knowledge is required for evaluating the external factors as well as operating the expert systems. Machine knowledge is automatically derived from historical instances of a target problem domain by using machine learning techniques, and used as a major knowledge source for inference. Expert knowledge is incorporate dinto fuzzy membership functions for external factors which seem to significantly affect the target problems. We applied this mechanism to a prototyoe expert system whose major objective is to provide expert guidance for stock market timing such as sell, buty, or wait. Experiments showed that our proposed mechanism can improve the solution quality of expert systems operating in turbulent decision-making environments.

• Journal of the Microelectronics and Packaging Society
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• v.8 no.3
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• pp.11-17
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• 2001

The design and manufacture of injection molded polymeric parts with desired properties is a costly process dominated by empiricism, including the repeated modification of actual tooling. This paper presents an expert design evaluation system which can predict the mechanical performance of a molded product and diagnose the design before the actual mold is machined. The knowledge-based system synergistically combines a rule-based expert system with CAE programs. Heuristic knowledge of injection molding is formalized as rules of an expert consultation system. The expert system interprets the analytical results of the process simulation, predicts the performance, evaluates the design and generates recommendations for optimal design alternatives.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.2
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• pp.99-107
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• 1992

Both simulation and expert systems are popular ways to solve complex and hard problems. However, the results of the simulation, which include a large amount of valuable information as a good knowledge source, are not used efficiently. Furthermore, the development of the expert systems can fail because there is no expert or an expert is not available. A new Simulation-Based Expert System(SIMBES) paradigm has been constructed to overcome these problems. It consists of simulator, feature extractor, machine learning system, performance evaluator and Knowledge-Based Expert System(KBES). A SIMBES was implemented for an existing schedule-based MRP system in Smalltalk/V to show how this paradigm works and experimented for a large number of jobs. The KBES and the existing system produced better schedules for 72 percent and 28 percent of the jobs, respectively.

• 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 Welding and Joining
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• v.10 no.4
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• pp.199-212
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• 1992

Expert system is a practical application part of the artificial intelligence and can be generally described as a computer-based system designed to simulate the knowledge and reasoning of a human expert, and to make that knowledge conveniently available to other people in a useful way. Expert systems consist of three major components, knowledge base, inference engine and user interface. In this paper, it is aimed to construct a prototype system to design the horizontal-typed pressure vessel. To do this, a representative artificial programming language, Turbo Prolog, was employed, and the knowledge representation was mainly done by the production rule such as "If(condition), than (action)" style and by the predicate logic. In the developed system, it was quite easy to represent the knowledge of "If(condition), then (action)"style and by the predicate logic. In the developed system, it was quite easy to represent the knowledge of "If(condition). then(action)" style and the various table-like data. It was also effective to represent the graphics. Though this expert system is by now small and incomplete, it is possible to expand it to a larger and refined system later.rger and refined system later.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.211-218
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• 2001

This paper introduces a method of constructing expert systems in an integrated environment for automatic software design. This integrated environment may be applicable from top-level system architecture design, data flow diagram design down to flow chart and coding. The system is integrated with three CASE tools, FSD (Functional Structure Diagram), DFD (Data Flow Diagram) and structured chart PAD (Problem Analysis Diagram), and respective expert systems with automatic design capability by reusing past design. The construction way of these expert systems is based on systematic acquisition of design knowledge stemmed from a systematic design work process of well-matured developers. The design knowledge is automatically acquired from respective documents and stored in the respective knowledge bases. By reusing it, a similar software system may be designed automatically. In order to develop these expert systems in a short period, these design knowledge is expressed by the unified frame structure, functions of th expert system units are partitioned mono-functions and then standardized components. As a result, the design cost of an expert system can be reduced to standard work procedures. Another feature of this paper is to introduce the integrated environment for automatic software design. This system features an essentially zero start-up cost for automatic design resulting in substantial saving of design man-hours in the resulting in substantial saving of design man-hours in the design life cycle, and the expected increase in software productivity after enough design experiences are accumulated.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.378-382
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• 2001

The purpose of this study was to develop an expert system supporting the diagnosis of diffuse interstitial lung disease by high resolution computed tomography. CLIPS(C language integrated production system) with rule-based reasoning was used to develop the system. Development of expert system had three stages knowledge acquisition, knowledge representation, and reasoning. Knowledge was obtained and integrated, from tables and figure legends of a representative textbook in the domain of this expert system, High-Resolution CT of the Lung, by Webb WR, Mueller NL, and Naidich DP. The acquired knowledge was analyzed to form a knowledge base. Overlapping knowledge was eliminated, similar pieces of knowledge were combined and professional terms were defined. The most important knowledge of findings was then selected for each disease. After groupings of combined findings were made, disease groups were analyzed sequentially to determine final diagnoses. The system was based upon the input of 69 diseases, 185 findings, 73 conditions, 387 status, and 62 rules. The system was set up to determine the diagnoses of diseases from the combination of findings using forward reasoning. In an empirical trial, the system was applied to support the diagnosis of 40 cases of diffuse interstitial lung diseases. The performance of two doctors with support of the system was compared to that of another two doctors without support of the system. The two doctors with the support of the system made more accurate diagnoses than the doctors without the support of the system. The system is believed to be useful for the diagnosis of rare diseases and for cases with many possible differential diagnoses. In conclusion, an expert system supporting the high resolution computed tomographic diagnosis of diffuse interstitial lung disease was developed and the system is thought to be useful for medical practice.

• Journal of Intelligence and Information Systems
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• v.9 no.2
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• pp.19-38
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• 2003

In this research, we propose the mechanism to develop self-evolving expert systems (SEES) based on data mining (DM), fuzzy neural networks (FNN), and relational database (RDB)-driven forward/backward inference engine. Most researchers had tried to develop a text-oriented knowledge base (KB) and inference engine (IE). However, this approach had some limitations such as 1) automatic rule extraction, 2) manipulation of ambiguousness in knowledge, 3) expandability of knowledge base, and 4) speed of inference. To overcome these limitations, knowledge engineers had tried to develop an automatic knowledge extraction mechanism. As a result, the adaptability of the expert systems was improved. Nonetheless, they didn't suggest a hybrid and generalized solution to develop self-evolving expert systems. To this purpose, we propose an automatic knowledge acquisition and composite inference mechanism based on DM, FNN, and RDB-driven inference engine. Our proposed mechanism has five advantages. First, it can extract and reduce the specific domain knowledge from incomplete database by using data mining technology. Second, our proposed mechanism can manipulate the ambiguousness in knowledge by using fuzzy membership functions. Third, it can construct the relational knowledge base and expand the knowledge base unlimitedly with RDBMS (relational database management systems) module. Fourth, our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy relationships. Fifth, RDB-driven forward and backward inference time is shorter than the traditional text-oriented inference time.

• Journal of Korean Society on Water Environment
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• v.23 no.1
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• pp.103-110
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• 2007

An efficient operational strategy using expert system for metro water supply systems in case of emergency situations is developed in this study. The emergency situations of the water supply systems are classified into three categories : pipeline system accident, machinery and electric facility accident and water quality accident. A PC-based expert system is developed using CLIPS for Seoul metro water supply system, Phase 1 & 2 system and Phase 3 & 4 system. Broad professional knowledges and experiences from the experts in the water supply systems have been collected systematically to construct the knowledge base. Decision-making in case of an emergency is based upon the professional knowledge so that a rational and efficient operational management can be available even in the absence of experienced expert. Especially the expert model developed in this study also provides a guide for pumping operation in case of pipeline accident to confirm that the proper pressure to all nodes in the system is supplied. The pipe network simulator KYPIPE has been consecutively executed by trial and error fashion for each pipeline in the system. The results from KYPIPE were included in the knowledge base to supplement the knowledge of the field engineers.

• 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.