• Ocean Systems Engineering
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• v.9 no.2
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• pp.179-190
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• 2019

This paper deals with the problem of the global stabilization for a class of ocean structure systems. It is well known that, in general, the global asymptotic stability of the ocean structure subsystems does not imply the global asymptotic stability of the composite closed-loop system. The classical fuzzy inference methods cannot work to their full potential in such circumstances because given knowledge does not cover the entire problem domain. However, requirements of fuzzy systems may change over time and therefore, the use of a static rule base may affect the effectiveness of fuzzy rule interpolation due to the absence of the most concurrent (dynamic) rules. Designing a dynamic rule base yet needs additional information. In this paper, we demonstrate this proposed methodology is a flexible and general approach, with no theoretical restriction over the employment of any particular interpolation in performing interpolation nor in the computational mechanisms to implement fitness evaluation and rule promotion.

• International Journal of Safety
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• v.6 no.2
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• pp.27-32
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• 2007

For last several decades with the achievement of fast economic development, the electrical fires occupies over 30 percent of total fire incidents almost every year in Korea and not decreased in spite of much times and efforts. Electrical fire cause diagnostics are to confirm a cause for the fire by examination of fire scene. Cause diagnosis methods haven't been systematized yet, because of limits for available information, investigator's biased knowledge, etc. Therefore, in order to assist the investigators and to find out the exact causes of electrical fires, required is research for an electrical fire cause diagnosis system using DB, computer programming and some mathematical tools. The electrical fire cause diagnosis system has two functions of DB and electrical fire cause diagnosis. The cause diagnosis is conducted by a case-based reasoning on a case base and rule-based reasoning on a rule base. For the diagnosis with high reliability, a mixed reasoning approach of a case-based reasoning and fuzzy rule-based reasoning has been adopted. The electrical fire cause diagnosis system proposes the electrical fire causes inferred from the diagnosis processes, and possibility of the causes as well.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.5
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• pp.50-58
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• 1998

A proper model of expert system for the very thin sheet metal press die design has been suggested. Using the suggested model, an expert system of the very thin sheet metal press die has been developed. This study contains that the results from the developed system for three kinds of specimens have the adaptability in the actual site. In addition, the possibility for expansion of this system has been discussed. The developed system, which is based on the knowledge base, has been included in a lot of expert's technology in the practice field. C-language under the HP-UNIX system and CIS customer language of the EXCESS CAD/CAM system have been used as the overall CAD environment. Results from this system will provide effective aids to the designer in this field.

• The Transactions of the Korea Information Processing Society
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• v.7 no.5
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• pp.1434-1445
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• 2000

An expert system executes the inference, based on the knowledge of specific domain. the reliability on the results of inference depends upon both the consistency and accuracy of knowledge. This is the reason why expert system requires the facilities which can practice an access to the various kinds of knowledge and maintain the consistency and accuracy of knowledge an maintain the consistency and accuracy of knowledge. This paper is to implement an expert system permitting an access of declarative and procedural knowledge in the knowledge base and in the data base. This paper is also to implement a knowledge acquisition system which adds the knowledge a only if its accuracy and consistency are maintained, after verifying the potential errors such as contradiction, redundancy, circulation, non-reachable rule and non-lined rule. In consequence, the expert system realizes a good access to the various sorts of knowledge and increases the reliability on the results of inference. The knowledge acquisition system contributes tro strengthening man-machine interface that enables users to add the knowledge easily to the knowledge base.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.25-29
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• 2001

There are so many researches about the search method for the most compatible dispatching rule to a manufacturing system state. Most of researches select the dispatching rule using simulation results. This paper touches upon two research topics: the clustering method for manufacturing system states using simulation, and the search method for the most compatible dispatching rule to a manufacturing system state. The manufacturing system state variables are given to ART II neural network as input. The ART II neural network is trained to cluster the system state. After being trained, the ART II neural network classifies any system state as one state of some clustered states. The simulation results using clustered system state information and those of various dispatching rules are compared and the most compatible dispatching rule to the system state is defined. Finally there are made two knowledge bases. The simulation experiments are given to compare the proposed methods with other scheduling methods. The result shows the superiority of the proposed knowledge base.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.11b
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• pp.633-639
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• 2001

This paper proposes a knowledge-based expert system. which is assembled into hardware organized with sensor module. AID converter, USB. data acquisition PC and software composed of monitoring and diagnosis module combined with a frame-based method using Sohre's chart and a rule-based method. Vibration signals using various sensors are acquired by AID converter. transferred into PC and processed to obtain a continuous monitoring of the machine status displayed into several plots. Through combining frame-base which covers wide vibration causes with rule-base which gives relatively specified diagnosis results, high accuracy of fault diagnosis can be guaranteed and knowledge base can be easily extended by adding new causes or symptoms. Some examples using experimental data show the good feasibility of the proposed algorithm for condition monitoring and diagnosis of industrial rotating machinery.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.296-301
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• 1989

As a cornerstone of assembly automation, the automatic part feeders are used to feed the various kind of the parts to the assembly workstation in the desired order and fashion. In this paper, EXPERT SYSTEM consisting of the data base for the feeding functions and part properties plus the rule base for the selection of feeder types is developed. The symbolic data of the part properties are used as basic factors in the selection rule of the suitable feeder types.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.162-165
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• 1996

In this paper, we proposed an optimization method of the membership function and the numbers of fuzzy rule base for the stabilization controller of the inverted pendulum system by genetic algorithm(GAs). Conventional methods to these problems need to an expert knowledge or human experience. The proposed genetic algorithm method will tune automatically the input-output membership parameters and will optimize their rule-base.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1997.10a
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• pp.315-320
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• 1997

Rule minimization technique adapted from rough set theory was applied to remove redundant knowledge which is not necessary to make a knowledge base. New algorithm to diagnose fault using Improved Fuzzy Cognitive Maps(I-FCMs), and Fuzzy Associative Memory(FAM) is proposed. I-FCM[22] is superior to gathering knowledge from many experts and descries dynamic behaviors of systems very well. I-FCM is not only a knowledge base, but also a inference engine. FAM has learning capability like neural network[12]. Rule minimization and composition of I-FCM and FAM make it possible to construct compact knowledge base and breaks the border between inference engine and knowledge base.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.18-25
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• 1992

In this paper, a rule checker which aids in composing a consistent knowledge base by checking redundancies and inconsistencies in a knowledge base is proposed. The proposed algorithm checks the rules by representing the rule connections as a network . The standard model of the rules adapted in this algorithm is in the Conjunctive Normal Form which includes NOT's, and rules of conventional expert system can be checked by converting them into the standard form by a rule form at converter. When compared with Ginsberg's KB-reducer which is conceptually most similar to the proposed algorithm among existing methods,it is shown by a computer simulation that with 360 rules, the checking time is three times faster and the rate increased as the number of rules increased, but the total memory requirement of the proposed agorithm is 1.2 times larger. The proposed algorithm has further advantages in that it can check circular rule chains and can find the paths of the redundant and inconsistent rules.