• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.173-178
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• 1995

The verification phase of knowledge base is an important part for developing reliable expert systems, especially in nuclear industry. Although several strategies or tools have been developed to perform potential ewer checking, they often neglect the reliability of verification methods. Because a Petri net provides a uniform mathematical formalization of knowledge base, it has been employed for knowledge base verification. In this work, we devise and suggest an automated tool, called COKEP (Checker Of Knowledge base using Extended Petri net), for detecting incorrectness, inconsistency, and incompleteness in a knowledge base. The scope of the verification problem is expanded to chained errors, unlike previous studies that assumed error incidence to be limited to rule pairs only. In addition, we consider certainty factor in checking, because most of knowledge bases have certainty factors.

• Nuclear Engineering and Technology
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• v.28 no.6
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• pp.522-531
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• 1996

The adoption of expert systems mainly as operator supporting systems is becoming increasingly popular as the control algorithms of system become more and more sophisticated and complicated. The verification phase of knowledge base is an important part for developing reliable expert systems, especially in nuclear industry. Although several strategies or tools have been developed to perform potential error checking, they often neglect the reliability of verification methods. Because a Petri net provides a uniform mathematical formalization of knowledge base, it has been employed for knowledge base verification. In this work, we devise and suggest an automated tool, called COKEP(Checker Of Knowledge base using Extended Petri net), for detecting incorrectness, inconsistency, and incompletensess in a knowledge base. The scope of the verification problem is expanded to chained errors, unlike previous studies that assume error incidence to be limited to rule pairs only. In addition, we consider certainty factor in checking, because most of knowledge bases have certainty factors.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.241-245
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• 1989

A knowledge based expert system is a computer program that emulates the reasoning process of a human expert in a specific problem domain. This paper presents an expert system to diagnose the various faults in power system. The developed expert system is represented considering two points; the possibility of solution and the fast processing speed. As uncertainties exist in the facts and rules which comprise the knowledge base of the expert system, Certainty Factor, which is based on the confirmation theory is used for the inexact reasoning. Also, as the diagnosis problem requires the inductive reasoning process in nature, the solution is imperfect and not unique in general. So the expert system is designed to generate all the possible hypothesis in order of the possibility and also it can explain the propagation procedure of the faults for each solution using the built in backtracking mechanism. In realization of the expert system, the processing speed is greatly dependent upon the problem representation, reasoning scheme and search strategy. So, in this paper the fault diagnosis problem itself is analysed from the view point of Artificial Intelligence and as a result, the expert system has the following basic features. 1) The certainty factor is adopted in the inference engine for inexact reasoning. 2) Problem apace is represented using the problem reduction technique. 3) Bidirectional reasoning scheme is used. 4) Best first search strategy is adopted for rapid processing. The expert system was developed us ing PROLOG language.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.4
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• pp.368-373
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• 2000

In this paper, a control algorthm suitable for multi-objective control is proposed based on the orthogonal array which is normally used in statics and industrial engineering. And a newly defined Nthcertainty factor is suggested, which can effectively exclude the less confident rule. The Nth-certainty factor is defined by the F-values of the ANOVA(analysis of variance) table. It is shown that the algorithm can be successfully adopted to the design of controller for an active magnetic bearing system.

• Korean Journal of Remote Sensing
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• v.15 no.2
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• pp.91-105
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• 1999

Spatial data integration using multiple geo-based data sets has been regarded as one of the primary GIS application issues. As for this issue, several integration schemes have been developed as the perspectives of mathematical geology or geo-mathematics. However, research-based approaches for statistical/quantitative assessments between integrated layer and input layers are not fully considered yet. Related to this niche point, in this study, spatial data integration using multiple geoscientific data sets by known integration algorithms was primarily performed. For spatial integration by using raster-based GIS functionality, geological, geochemical, geophysical data sets, DEM-driven data sets and remotely sensed imagery data sets from the Ogdong area were utilized for geological thematic mapping related by mineral potential mapping. In addition, statistical/quantitative information extraction with respective to relationships among used data sets and/or between each data set and integrated layer was carried out, with the scope of multiple data fusion and schematic statistical assessment methodology. As for the spatial integration scheme, certainty factor (CF) estimation and principal component analysis (PCA) were applied. However, this study was not aimed at direct comparison of both methodologies; whereas, for the statistical/quantitative assessment between integrated layer and input layers, some statistical methodologies based on contingency table were focused. Especially, for the bias reduction, jackknife technique was also applied in PCA-based spatial integration. Through the statistic analyses with respect to the integration information in this case study, new information for relationships of integrated layer and input layers was extracted. In addition, influence effects of input data sets with respect to integrated layer were assessed. This kind of approach provides a decision-making information in the viewpoint of GIS and is also exploratory data analysis in conjunction with GIS and geoscientific application, especially handing spatial integration or data fusion with complex variable data sets.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.05a
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• pp.85-89
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• 2006

구간값 퍼지집합은 일반적인 퍼지집합보다 언어적인 의사결정 절차에서 매핑의 정확성과 계산의 효율성이 뛰어나고, 규칙의 가중치는 패턴 분류문제에서 분류 경계를 효율적으로 조정할 수 있다는 장점을 가지고 있다. 따라서 본 논문에서는 퍼지규칙 기반 분류방법을 구간값 퍼지규칙 기반 분류방법으로 확장하고 규칙의 가중치를 고려한 분류방법을 제안한다. 모의실험에서는 일반 퍼지집합에서 규칙 가중치를 고려한 분류방법과 구간값 퍼지집합에서 규칙 가중치를 고려한 분류방법을 비교하였다.

• Asia pacific journal of information systems
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• v.8 no.3
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• pp.135-145
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• 1998

There exists popular approach using certainty factor (CF) for the development of effective reasoning mechanism under uncertainty in Expert System, However, there is a problem with CF. The CF values could be resulted in the opposite of given conditional probabilities. In this paper, a method for, reasoning under uncertainty using reliability theory to overcome the problem is proposed. And the proposed method is used in the development of Expert System for the selection of equipment for automated warehouses.

• Journal of Electrical Engineering and information Science
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• v.2 no.5
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• pp.45-50
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• 1997

This paper present an advanced fault diagnosis expert system to assist the operators at local control center. The system utilizes all th information available in a local control center for the better diagnostic performance. The major feature of the system is dealing with multiple faults diagnosis based on the certainty factor method for the reasoning process. the overall performance and the generality are also enhanced by utilizing the general topological knowledge. ASCADA simulator is also developed for he test and demonstration.

• 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.

• Transactions of the Korean Society of Mechanical Engineers
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• v.15 no.6
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• pp.2026-2036
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• 1991

An expert system is developed which can diagnose the causes and remedies of the failures of power transmission gears. The basic components of the expert system are knowledge base, inference engine, and working memory. The knowledges in knowledge base are classified into the knowledges for determining the failure types and for diagnosis of causes and remedies of the failures. The former is represented hierarchically into the main category of eleven groups by rules and the sub category of twenty four groups by facts, while the later is represented by facts according to the each group of knowledges. In the inference engine some considerations are implemented, i.e., the backward chaining method and depth first search to determine the category of the failures, the meta-knowledges to shorten the search space, the certainty factor to evaluate the reliability of result, and the unification strategy to diagnose the causes and remedies of the failures. The working memory is established to hold the results during inference temporarily. In addition, knowledge acquisition facility, explanation facility, and user interface are included for the usefulness of user. This expert system is written with the PROLOG programming language on IBM-PC compatible computer operated by MS-DOS and be executed alone.