• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12B
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• pp.1219-1226
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• 2010

It is necessary to implementation of system contain intelligent decision making algorithm because discriminant and prediction system for Red Tide is insufficient development and the study of red tide are focused for the investigation of chemical and biological causing. In this paper, we designed inference system using case based reasoning method and implemented knowledge base that case for Red Tide. We used K-Nearest Neighbor algorithm for recommend best similar case and input 375 EA by case for Red Tide case base. As a result, conducted 10-fold cross verification for minimal impact from learning data and acquired confidence, we obtained about 84.2% average accuracy for Red Tide case and the best performance results in case by number of similarity classification k is 5. And, we implemented Red Tide monitoring system using inference result.

• The Korean Journal of Financial Studies
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• v.3 no.2
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• pp.267-279
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• 1996

The prediction of future demand is a vital task in managing business operations. To this end, traditional approaches often focused on statistical techniques such as exponential smoothing and moving average. The need for better accuracy has led to nonlinear techniques such as neural networks and case based reasoning. In addition, experimental design techniques such as orthogonal arrays may be used to assist in the formulation of an effective methodology. This paper investigates a multistrategy approach involving neural nets, case based reasoning, and orthogonal arrays. Neural nets and case based reasoning are employed both separately and in combination, while orthoarrays are used to determine the best architecture for each approach. The comparative evaluation is performed in the context of an application relating to the prediction of Treasury notes.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.5
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• pp.163-170
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• 2005

Urban transit is a complex system that is combined electrically and mechanically, it is necessary to construct maintenance system for securing safety accompanying high-speed driving and maintaining promptly. Expert system is a computer program which uses numerical or non-numerical domain-specific knowledge to solve problems. In this research, we intend to develop the expert system which diagnose failure causes quickly and display measures. For the development of expert system, standardization of failure code classification system and creation of BOM(Bill Of Materials) have been first performed. Through the analysis of failure history and maintenance manuals, knowledge base has been constructed. Also, for retrieving the procedure of failure diagnosis and repair linking with the knowledge base, we have built RBR(Rule Based Reasoning) engine by pattern matching technique and CBR(Case Based Reasoning) engine by similarity search method. This system has been developed based on web to maximize the accessibility.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.774-779
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• 2001

If rotating machinery have a fault, we can detect it using vibration or noise signals. However some maintenance engineers who doesn't have expert knowledge, needs the help of vibration experts for diagnosing rotating machinery. But qualified experts are rare, therefore we have been developed the case based reasoning (CBR) system which is able to manipulate the past experiences of vibration diagnosis experts. In the CBR system, the maintenance engineers can retrieve too information from previous cases which are most similar to new problem and they can solve new problem using solutions from the previous cases. In this paper, we propose a new method which is the case retrieval of CBR system using Petri net and we also applied it to diagnosis for electric motors as a practical problem.

• 한국경영정보학회:학술대회논문집
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• 2007.11a
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• pp.591-596
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• 2007

본 연구에서는 상황 추론의 기능을 추천 시스템에 접목하였다. 연구의 대상 영역은 음악 추천 분야인데, 본 연구에서 제안하는 시스템은 세 개의 모듈, 즉 Intention Module, Mood Module 그리고 Recommendation Module로 구성되어 있다. Intention Module은 사용자가 음악을 청취할 의향이 있는지 없는지를 외부 환경의 상황 데이터를 이용하여 추론한다. Mood Module은 사용자의 상황에 적합한 음악의 장르를 추론한다. 마지막으로 Recommendation Module은 사용자에게 선정된 장르의 음악을 추천한다.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.7
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• pp.282-287
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• 2007

Information society is dramatically developing in the various areas of finance, trade, medical service, energy, and education using information system. Evaluation for risk analysis should be done before security management for information system and security risk analysis is the best method to safely prevent it from occurrence, solving weaknesses of information security service. In this paper, Modeling it did the evaluation-base CBD function it will be able to establish the evaluation plan of optimum. Evaluation-based CBD(case-based reasoning) functions manages a security risk analysis evaluation at project unit. it evaluate the evaluation instance for beginning of history degree of existing. It seeks the evaluation instance which is similar and Result security risk analysis evaluation of optimum about under using planning.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.491-501
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• 2002

Case-based reasoning is emerging as a leading methodology for the application of artificial intelligence. CBR is a reasoning methodology that exploits similar experienced solutions, in the form of past cases, to solve new problems. Hybrid model achieves some convergence of the wide proliferation of credit evaluation modeling. As a result, Hybrid model showed that proposed methodology classify more accurately than any of techniques individually do. It is confirmed that proposed methodology predicts significantly better than individual techniques and the other combining methodologies. The objective of the proposed approach is to determines a set of weighting values that can best formalize the match between the input case and the previously stored cases and integrates fuzzy sit concepts into the case indexing and retrieval process. The GA is used to search for the best set of weighting values that are able to promote the association consistency among the cases. The fitness value in this study is defined as the number of old cases whose solutions match the input cases solution. In order to obtain the fitness value, many procedures have to be executed beforehand. Also this study tries to transform financial values into category ones using fuzzy logic approach fur performance of credit evaluation. Fuzzy set theory allows numerical features to be converted into fuzzy terms to simplify the matching process, and allows greater flexibility in the retrieval of candidate cases. Our proposed model is to apply an intelligent system for bankruptcy prediction.

• Knowledge Management Research
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• v.3 no.1
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• pp.93-106
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• 2002

Knowledge management is a recent area in business administration that deals with how to leverage knowledge as a key asset and resource in modern organizations. Also, Knowledge systems are the single most important industrial and commercial offspring of the discipline called artificial intelligence. A Case Based Reasoning(CBR) system solves new problems by recalling adapting previous solutions. This paper presents the results of a recent empirical study. Furthermore this study proposes a CBR Methodology designed to manage knowledge of Hana company under e-business.

• The Journal of Information Systems
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• v.4
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• pp.181-209
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• 1995

As the effective use of information has gained greater attention over the decade, various conventional AI techniques have been applied to develop expert systems for business applications. Case-based reasoning (CBR) makes data more accessible by organizing it as a set of examples from past experience that can be generalized and applied to current problems. This paper illustrates basic concepts of CBR and addresses the system discussed in this paper can provide a basis for building more flexible and adaptable expert systems for business applications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.129-138
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• 1999

The aim of this research is the development of an automated fixture planning system for prismatic parts using the case-based reasoning (CBR). CBR is the problem solving paradigm that uses the similarity between a new problem and old cases to solve the new problem. This research uses CBR for the fixture planning. A case is composed with the information of the part, the components of fixture and the method of fixing for the part. The basic procedure is the retrieval and adaptation for the case, and this research presents the method of retrieval that selects most similar case to the new situation. The retrieval-step is divided into an index matching and an aggregated matching. The adaptation is accomplished by the modification, which transforms the selected case to the solution of the situation of the input part by the specified CBR algorithm. The components of fixture and the method of fixing are determined for a new part by the procedure.