• Asia pacific journal of information systems
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• 제6권2호
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• pp.77-105
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• 1996

The accuracy of knowledge is a major concern for expert system developers and users. Machine learning approaches have recently been found to be useful in knowledge acquisition for expert systems. However, the accuracy of concept acquired from machine learning could not be analyzed in most cases. In this paper we develop a comprehensive knowledge error analysis methodology for practical use of expert systems. Decision tree induction is an important type of machine learning method for business expert systems. Here we start to analyze with knowledge acquired from decision tree induction method, and extend the results to develop error analysis methodology for general machine learning methods. We give several examples and illustrations for these results. We also discuss the applicability of these results to multistrategy learning approaches.

• 대한기계학회논문집
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• 제16권12호
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• pp.2252-2260
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• 1992

본 연구에서는 사출금형의 공정설계 전문가시스템의 개발에 대한 연구의 일부 로서, 구체적으로는 구조가 비교적 간단하고 의사결정 규칙의 획득이 용이한 받침판이 없는 2단 사출금형을 대상으로 하여 CLIPS를 사용하여 개인용 컴퓨터에서 실행이 가능 한 공정설계 전문가시스템을 개발하여 실제 사출금형 공정설계에 적용하여 그 유효성 을 평가하였다.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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• pp.189-197
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• 1998

The axiomatic hypothesis of the objective distribution of evaluation subjection will be proposed in this paper. On the basis of that, set up the random response model of the expert evaluation system and the quality control principle of expert base. Under this principle, develop the statistical quality control theory of expert base, further; provide the quality improvement technology for expert base.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권2호
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• pp.284-310
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• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• 한국생산제조학회지
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• 제19권1호
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• pp.94-100
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• 2010

Nowadays, several nontraditional machining(NTM) processes are widely used to machine a complex and accurate shape part of hard materials, such as titanium, ceramics, high strength temperature resistant and refractory materials which are difficult to machine and having high strength, hardness, toughness. Machining of these complex shapes in such materials by traditional machining processes are very difficult. The NTM processes is important in the areas of micro- and nano scale machining, where high accuracy and superior surface characteristics are required, which can only be achieved using these NTM processes. So, for effective selection of different NTM processes, careful decision making for a given NTM application is often necessary. An appropriate NTM process for a given material and shape condition is very difficult for the novice engineers. In this paper, an expert system based on an analytic network process(ANP) is suggested for a best selection of NTM process in a NTM application considering an prior interdependency effect among various factors.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 추계학술대회 논문집 학회본부
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• pp.118-121
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• 1988

Load forecasting is an important issue as for the economic dispatch and there have been many researches which are classfied into two classes, time series method and factor analysis method. But the former is not adaptive for a sudden change of a correlated factor and the latter is not inefficient as the factor estimation is not easy. To make matters worse, both of them are not good for the estimation of special days. It is because the load forecasting is not a problem modeled precisely in mathematics, but a problem requires experience and knowledge those can solve it case by case. In this viewpoint, an expert system is proposed which can use complicated experience of an expert by use of fuzzy decision.

• 산업경영시스템학회지
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• 제17권32호
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• pp.297-308
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• 1994

In the information system, there are many fields that used by decision making support system. Nowadays, the reasons that the need of the decision making system in audit is increased, are as follows. \circled1 The increased of competitiveness in audit environment \circled2 The rapid replenishment of computer hardware and computer system in corporations. The purposes of this study are as follows. \circled1 The connection of Internal management assess results and practical examination. \circled2 In the making of audit opinion, the establish of non-measure and evaluate logic. \circled3 The suggestion of knowledge base structure about the audit task. \circled4 The development of prototype system for the accounting audit expert system. The expected usefulness of accounting audit expert system development are as follows. \circled1 Audit time may be saved \circled2 The consistence of opinion will be increased \circled3 The elevation of audit technique \circled4 The decreased of audit risk \circled5 In the decision making rationlization of accounting information users, it will be proved as usefulness.

• 한국기계가공학회지
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• 제13권6호
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• pp.54-60
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• 2014

In industry, several casting process are widely used to manufacture complex and accurate blank part of hard materials such as aluminum, casting steels, bronze and magnesium alloys which are difficult to manufacture in a blank shape. Even if the casting process does not high accuracy superior surface characteristics other machining process, the casting process is widely used in manufacturing blank part. Furthermore, it is difficult to select appropriate casting process a part among several casting process. for effective selection different process, a careful decision given casting application is necessary. An appropriate casting for a given material and shape condition must be selected for novice engineers in industry. In this paper, an expert system based on an analytic network process(ANP) is suggested for best selection of casting considering a prior interdependency effect among various factors such as material, geometry, process capability, economy and equipment.

• 의료법학
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• 제13권2호
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• pp.115-139
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• 2012

Civil proceedings, surveyed results and medical expenses that are evidenced by expert witness are just one of the methods of proof. Since a judge makes decision by synthesizing all evidences on a concerned case, thus the judgement would be different from that of expert witness. It is not rational for medical institutions, of which priorities are medical treatment, to give priority to disability decision. However, despite of its importance, medical institutions less recognize about the necessity of procedural stability and predictability in expert valuation. It is necessary to identify actual problems and investigate rational alternatives to acquire fairness in valuation procedures and accuracy in calculating future medical expenses. Therefore, this research explores the problems and realities of evaluation process in medical treatments, and then discuss the alternatives of written expert opinion and estimation of future medical expenses.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권12호
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• pp.978-982
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• 2009

본 논문에서는 다수의 강화 학습 에이전트들의 학습 결과 및 Expert의 지식을 하나의 학습 알고리즘으로 융합하는 강화학습인 "potential-based" reinforcement learning(RL)기법에 불확실한 환경에서의 의사결정 알고리즘인 Case-based Decision Theory(CBDT)를 적용한 "RLs-CBDT"를 제안한다. 그리고 테트리스 실험을 통하여 기존의 RL 알고리즘에 비해 RLs-CBDT가 최적의 정책에 더 마르게 수렴하는 것을 보인다.