• Proceedings of the Korean Geotechical Society Conference
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• 2000.03b
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• pp.101-108
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• 2000

In this study, an expert system was developed to predict the safety of tunnel and choose proper tunnel reinforcement system using fuzzy quantification theory and fuzzy inference rule based on tunnel information database. The expert system developed in this study have two main parts named pre-module and post-module. Pre-module decides tunnel information imput items based on the tunnel face mapping information which can be easily obtained in-situ site. Then, using fuzzy quantification theory II, fuzzy membership function is composed and tunnel safety level is inferred through this membership function. The comparison result between the predicted reinforcement system level and measured ones was very similar. In-situ data were obtained in three tunnel sites including subway tunnel under Han river, This system will be very helpful to make the most of in-situ data and suggest proper applicability of tunnel reinforcement system developing more resonable tunnel support method from dependance of some experienced experts for the absent of guide.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.1
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• pp.1-7
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• 2011

Most of expert systems use the text-oriented knowledge bases. However, knowledge management using the knowledge bases is considered as a huge burden to the knowledge workers because it includes some troublesome works. It includes chasing and/or checking activities on Consistency, Redundancy, Circulation, and Refinement of the knowledge. In those cases, we consider that they could reduce the burdens by using relational database management systems-based knowledge management infrastructure and convert the knowledge into one of easy forms human can understand. Furthermore they could concentrate on the knowledge itself with the support of the systems. To meet the expectations, in this study, we have tried to develop a general-purposed knowledge conversion tool for expert systems. Especially, this study is focused on the knowledge conversions among text-oriented knowledge base, relational database knowledge base, and decision tree.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.29 no.1
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• pp.457-463
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• 2005

The use of the internet to facilitate commerce among companies promises vast benefits. Lots of e-marketplaces are building for several industries such as chemistry, airplane, and automobile industries. This study proposed new B2B EC business model for the shipping industry which concerns relatively massive fixed assets to be fully utilized. To be successful the proposed model gives participants to support useful information. To do this the expert system is constructed as the hybrid prediction system of neural network (NN) and memory based reasoning (MBR) with self-organizing map (SOM) and knowledge augmentaton technique using qualitative reasoning (QR). The expert system supports participants useful information coping with dynamic market environment. with this transportation companies are induced to participate in the proposed e-marketplace and helped for exchanges easily. Also participants would utilize their assets fully through B2B exchanges.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1169-1172
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• 2002

This paper presents the development of an expert system for monitoring and control of an oil production facility. The objectives of developing an expert system for the oil production facility are to monitor the Important processing parameters in different sections of the facilities and to control battery operations in real time. By providing consistent, fast, and reliable decision support to operators, the expert system can be used for automated monitoring and control of a petroleum production facility located south of Regina in Saskatchewan, Canada. The system was implemented in Visual Basic 6.0.

• Journal of the Korea Safety Management & Science
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• v.8 no.4
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• pp.181-193
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• 2006

The purpose of this thesis addresses a development of an expert system to support a decision making of the vender selection. The researches related to the vender selection problems have been studied and they provide 23 criteria to select proper venders. In this thesis, 8 criteria have been used to construct a knowledge base of the expert system. The system in this thesis consists of 6 steps in its procedure. Step 1 decides a specification that satisfies customer's needs and Step 2 chooses a part supplied by a vender. The type of an outside order is decided in Step 3 and some venders satisfying the customer's needs are selected in Step 4. Some of the venders chosen from step 4 which do not satisfy the fatal cirteria(that is Quality, Delivery, Price) can be deleted in Step 5. In the last step, 8 cirteria is used to select 3 venders according to their ranking. Consequently, this program provides for a man, who does not have the experiances, an efficient way to select appropriate venders in the vender selection problems.

• Geotechnical Engineering
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• v.10 no.3
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• pp.79-96
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• 1994

A tunnel design expert system entitled NESTED is developed using the artificial neural network. The expert system includes three neural network computer models designed for the stability assessment of underground openings and the estimation of correlation between the RMR and Q systems. The expert system consists of the three models and the computerized rock mass classification programs that could be driven under the same user interface. As the structure of the neural network, a multi -layer neural network which adopts an or ror back-propagation learning algorithm is used. To set up its knowledge base from the prior case histories, an engineering database which can control the incomplete and erroneous information by learning process is developed. A series of experiments comparing the results of the neural network with the actual field observations have demonstrated the inferring capabilities of the neural network to identify the possible failure modes and the support timing. The neural network expert system thus complements the incomplete geological data and provides suitable support recommendations for preliminary design of tunnels in rock masses.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.6
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• pp.781-788
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• 1999

In this paper, an expert system is proposed, which can be effectively applied to the large-scale systems with the diversity time constraints, the objectives and the unfixed system structure. The inference scheme of the expert system have the integrated structure composed of the intuitive inference module and logical inference module in order to support effectively the operating constraints of system. The intuitive inference module is designed using the pattern matching or pattern recognition method in order to search a same or similar pattern under the fixed system structure. On the other hand, the logical inference module is designed as the structure with the multiple inference mode based on the heuristic search method in order to determine the optimal or near optimal control strategies satisfing the time constraints for system events under the unfixed system structure, and in order to use as knowledge generator. Here, inference mode consists of the best-first, the local-minimum tree, the breadth-iterative, the limited search width/time method. Finally, the application results for large-scale distribution SCADA system proves that the inference scheme of the expert system is very effective for the large-scale system. The expert system is implemented in C language for the dynamic mamory allocation method, database interface, compatability.

• Journal of Intelligence and Information Systems
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• v.12 no.4
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• pp.127-136
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• 2006

This paper describes the result of a case study for developing an expert system framework in order to support Korean Army tactical C4I system. Korean Army had developed an expert system, STAFS(Situation & Threat Assessment Fusion Expert System), for supporting field intelligence analysis activities which has been implemented through traditional manual process inside the division level combat briefing room. STAFS, however, has serious limitations for supporting combat commander's decision making processes because of its limited capabilities, since the system had been developed for supporting only intelligence analysis function rather than for integrated combat decision making processes inside the combat briefing room. Thus, this paper proposed an integrated expert system framework for supporting the commander's decision making by addressing various activities implemented in the briefing room.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.21 no.9
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• pp.1373-1384
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• 1997

There have been a number of expert systems which are concerned with the design of machine elements such as gear, shaft, bearing and so on. However the design of more complicated systems such as gear dreives are still difficult. Thus, in consideration of the integrative nature of the system, we develop a design support system for gear drives which is composed of various machine elements-gear, shaft, bearing, key and so on. Design systems for each machine element are developed and integrated through object-oriented approach. Databases essential for data reference and/or data control in the design process are built up independently and interface to the main program. Expert systems are also developed and integrated for intelligent support to the designer, in those of the determination of gear specification and the selection of bearing types. Through the integration of design environment for each machine element, it is expected to increase the convenience in the design process and the stability of the design solution. And also the system management, including addition of various design/analysis modules and expansion to the gear drives of other types, can be conveniently achieved since the system has developed under due consideration of its efficiency and expandability through object-oriented programming approach.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.20-30
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• 2005

In the anaerobe identification, when we develop the clinical decision support system for department of laboratory medicine, we must consider expression of an incomplete knowledge structure and addition of an evolving knowledge based on an expert's informal and heuristic knowledge is very complicated work flow. In the present study, we developed the system for anaerobe identification to advise on identification of unknown bacillus using knowledge base and inference engine. In the future, we are planning to develop the clinical decision support system for the whole bacteria not only an anaerobe but also aerobe to offer an expert's static and dynamic knowledge.