• Title/Summary/Keyword: Case Based Reasoning

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Design and Implementation of Case-Based Reasoning System for Knowledge Management : The Case Study of Plant Construction Division of 'H' Cooperation (지식경영을 위한 사례기반추론 시스템의 설계 및 구축 : 'H'기업의 플랜트 건설 프로젝트 적용사례)

  • Jang, Gil-San
    • The Journal of Information Systems
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    • v.18 no.3
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    • pp.231-249
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    • 2009
  • Recently, plant construction industries are enjoying a favorable business climate centering around developing countries and oil producing countries rich in oil money. This paper proposes a methodology of implementing case-based reasoning(CBR) system for managing knowledge like lessons learned and various documents accumulated in performing power plant construction projects which are receiving a lot of order from foreign countries such as the Middle East, etc. Our methodology is consisted of 10 steps : user requirement gathering, information modeling, case modeling, case base design, similarity function design, user interface design, case base building, CBR module development, user interface implementation, integration test. Also, to illustrate the effectiveness of proposed methodology, the real CBR system is implemented for the plant business division of 'H' company which has international competitiveness in the field of plant construction industry. At present, the implemented CBR system is successfully utilizing as storing, sharing, and reusing knowledge which is accumulated in performing power plant construction projects in the target enterprise.

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Fixture Planning Using Case-Based Reasoning (사례기반 추론방법을 이용한 치공구의 선정)

  • 현상필;이홍희
    • 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.

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A Study for 8 Constitution Medicine Diagnosis Expert System Development(2) (8체질 진단을 위한 전문가 시스템 개발에 관한 연구(2))

  • Shin, Yong-Sup;Park, Young-Bae;Park, Young-Jae;Kim, Min-Yong;Lee, Sang-Chul;Oh, Hwan-Sup
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.12 no.2
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    • pp.107-126
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    • 2008
  • Background : There was seldom study about method that diagnose 8 Constitution beside method of pulse diagnosis in 8 Constitution Medicine. Objectives : This study is to make out 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning). Methods : First, at case base construction process we constructed case base for CBR embodiment because gathering 925 cases all to patient who constitution is verified, and second, at study model establishment process superior expert system development by purpose CBR of reasoning process dividing fundamental type CBR that spend basis data value and expert type CBR that reflect weight in basis data value accordin I II III to advice expert opinion, and third, system embodiment process explained about way to give process and weight that diagnose constitution through Nearest Neighbor Method sampling process of CBR techniques, and fourth, at system estimation process we selected superior CBR model because comparing and estimate the diagnosis rate of expert system with fundamental type system (GECBR) model and expert type I II III CBR system (AVCBR, AACBR, AGCBR) model that reflect expert opinion in fundamental type system. GECBR and AGCBR chose on superior study model. Through such 4 study process, we developed 8 constitution diagnosis expert system lastly. Results : 1. When we select GECBR that is fundamental type by reasoning system, diagnosis rate 78.91% of 8 constitution diagnosis expert system is expected, and the constitution diagnosis rate Hepatonia 90.4%, Cholecystonia 63.0%, Pancreotonia 91.1%, Gastrotonia 0%, Pulmotonia 71.2%, Colonotonia 74.4%, Renotonia 37.5%, Vesicotonia 67.1% expect. 2. When we select AGCBR that is expert type III by reasoning system, diagnosis rate 77.51% of 8 constitution diagnosis expert system is expected, and the constitution diagnosis rate Hepatonia 93.4%, Cholecystonia 58.5%, Pancreotonia 91.1%, Gastrotonia 0%, Pulmotonia 73.1%, Colonotonia 64.4%, Renotonia 41.7%, Vesicotonia 72.2% expect. Conclusion : Based on this study, 8 constitution diagnosis expert system may give help to diagnose 8 constitution, and it is going to utilize as objective estimation tool of 8 constitution diagnosis, and further study for 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning) is needed to supplement this study.

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A Study for 8 Constitution Medicine Diagnosis Expert System Development (8체질의학을 위한 진단 전문가 시스템 개발 및 고찰)

  • Shin, Yong-Sup;Park, Young-Bae;Park, Young-Jae;Kim, Min-Yong;Oh, Hwan-Sup
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.12 no.1
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    • pp.142-184
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    • 2008
  • Background: There was seldom study about method that diagnose 8 Constitution beside method of pulse diagnosis in 8 Constitution Medicine. Objectives: This study is to make out 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning). Methods: First, at case base construction process we constructed case base for CBR embodiment because gathering 925 cases all to patient who constitution is verified, and second, at study model establishment process superior expert system development by purpose CBR of reasoning process dividing fundamental type CBR that spend basis data value and expert type I II III CBR that reflect weight in basis data value according to advice expert opinion, and third, system embodiment process explained about way to give process and weight that diagnose constitution through Nearest Neighbor Method sampling process of CBR techniques, and fourth, at system estimation process we selected superior CBR model because comparing and estimate the diagnosis rate of expert system with fundamental type system (GECBR) model and expert type I II III CBR system (AVCBR, AACBR, AGCBR) model that reflect expert opinion in fundamental type system. GECBR and AGCBR chose on superior study model. Through such 4 study process, we developed 8 constitution diagnosis expert system lastly. Results: 1. When we select GECBR that is fundamental type by reasoning system, diagnosis rate 78.91% of 8 constitution diagnosis expert system is expected, and the constitution diagnosis rate Hepatonia 90.4%, Cholecystonia 63.0%, Pancreotonia 91.1%, Gastrotonia 0%, Pulmotonia 71.2%, Colonotonia 74.4%, Renotonia 37.5%, Vesicotonia 67.1% expect. 2. When we select AGCBR that is expert type III by reasoning system, diagnosis rate 77.51% of 8 constitution diagnosis expert system is expected, and the constitution diagnosis rate Hepatonia 93.4%, Cholecystonia 58.5%, Pancreotonia 91.1%, Gastrotonia 0%, Pulmotonia 73.1%, Colonotonia 64.4%, Renotonia 41.7%, Vesicotonia 72.2% expect. Conclusion: Based on this study, 8 constitution diagnosis expert system may give help to diagnose 8 constitution, and it is going to utilize as objective estimation tool of 8 constitution diagnosis, and further study for 8 Constitution Medicine Diagnosis Expert System Development used CBR(Case based Reasoning) is needed to supplement this study.

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Robustness of Learning Systems Subject to Noise:Case study in forecasting chaos

  • Kim, Steven H.;Lee, Churl-Min;Oh, Heung-Sik
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1997.10a
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    • pp.181-184
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    • 1997
  • Practical applications of learning systems usually involve complex domains exhibiting nonlinear behavior and dilution by noise. Consequently, an intelligent system must be able to adapt to nonlinear processes as well as probabilistic phenomena. An important class of application for a knowledge based systems in prediction: forecasting the future trajectory of a process as well as the consequences of any decision made by e system. This paper examines the robustness of data mining tools under varying levels of noise while predicting nonlinear processes in the form of chaotic behavior. The evaluated models include the perceptron neural network using backpropagation (BPN), the recurrent neural network (RNN) and case based reasoning (CBR). The concepts are crystallized through a case study in predicting a Henon process in the presence of various patterns of noise.

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Knowledge-Based Model for Forecasting Percentage Progress Costs

  • Kim, Sang-Yong
    • Journal of the Korea Institute of Building Construction
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    • v.12 no.5
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    • pp.518-527
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    • 2012
  • This study uses a hybrid estimation tool for effective cost data management of building projects, and develops a realistic cost estimation model. The method makes use of newly available information as the project progresses, and project cost and percentage progress are analyzed and used as inputs for the developed system. For model development, case-based reasoning (CBR) is proposed, as it enables complex nonlinear mapping. This study also investigates analytic hierarchy process (AHP) for weight generation and applies them to a real project case. Real case studies are used to demonstrate and validate the benefits of the proposed approach. By using this method, an evaluation of actual project performance can be developed that appropriately considers the natural variability of construction costs.

Computation and Verification of Approximate Construction cost of Steel Box Girder Bridge by Using Case-Based Reasoning (사례기반추론을 이용한 강박스거더교의 개략공사비 산정 및 검증)

  • Jung, Min-Sun;Kyung, Kab-Soo;Jeon, Eun-Kyoung;Kwon, Soon-Cheol
    • Journal of Korean Society of Steel Construction
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    • v.23 no.5
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    • pp.557-568
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    • 2011
  • To effectively come up with and secure a national budget, it is very important to estimate the reasonable construction cost of each step in public construction projects. In this study, the approximate construction cost of a steel box girder bridge in the early stages of the project, on which available information is limited, was proposed using case-based reasoning. In addition, construction cost estimation models were used for existing sample design models, and the accuracy of the estimation model for the presented cost was verified. The analysis results showed that the error rate was comparatively stable. Therefore, it is expected that construction cost estimation will be effectively suggested in the country's budget preparation.

Approximate Estimating Model Using the Case Based Reasoning - PSC BEAM Bridge - (사례기반추론을 이용한 개략공사비 산정모델 개발 - PSC BEAM교를 중심으로 -)

  • Kang, Chan-Sung;Lee, Geon-Hee;Kim, Kyoung-Min;Kim, Kyong-Ju
    • Proceedings of the Korean Institute Of Construction Engineering and Management
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    • 2008.11a
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    • pp.445-448
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    • 2008
  • This study attempts to estimate approximate cost on construction of PSC BEAM Bridge using Case-Based Reasoning and suggests approximate estimation model at the planning and design stage. This paper suggests phased influence factors on construction cost and approximate estimation model for integrated project cost management.

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A Study on Risk Analysis Methode Using Case-Based Reasoning (사례기반 추론을 이용한 위험분석방법 연구)

  • Lee, Hyeak-Ro;Ahn, Seong-Jin
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.18 no.4
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    • pp.135-141
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    • 2008
  • The risk enlargement of cyber infringement and hacking is one of the latest hot issues. To solve the problem, the research for Security Risk Analysis, one of Information Security Technique, has been activating. However, the evaluation for Security Risk Analysis has many burdens; evaluation cost, long period of the performing time, participants’ working delay, countermeasure cost, Security Management cost, etc. In addition, pre-existing methods have only treated Analyzing Standard and Analyzing Method, even though their scale is so large that seems like a project. the Analyzing Method have no option but to include assessors’ projective opinion due to the mixture using that both qualitative and quantitative method are used for. Consequently, in this paper, we propose the Security Risk Analysis Methodology which manage the quantitative evaluation as a project and use Case-Based Reasoning Algorithm for define the period of the performing time and for select participants.

Fuzzy Indexing and Retrieval in CBR with Weight Optimization Learning for Credit Evaluation

  • Park, Cheol-Soo;Ingoo Han
    • 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.

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