• Title/Summary/Keyword: Domain Expert

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A Study on the Blocker Design of Closed Die Forging with Discrete Wavelet Transform (이산 웨이블릿 변환을 이용한 형단조 공정의 예비성형용 금형 설계에 관한 연구)

  • 한상훈;임성한;오수익
    • Proceedings of the Korean Society for Technology of Plasticity Conference
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    • 2003.05a
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    • pp.27-33
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    • 2003
  • In closed-die forging process, blocker has been used to fill and distribute metal well in finisher die. Generally, the blocker shape was determined by an expert with many experiences. However, the manual blocker design process takes much time and efforts, so various automatic methods for the blocker design process have been suggested for the last three decades. The method with filtering in FFT (Fast Fourier Transform) for the blocker design provides general solution than other methods. But, due to the properties of FFT in time-frequency domain, this method has some drawbacks such as long calculation time, difficulty of local control and additional boundary process after filtering. In this study, DWT (Discrete Wavelet Transform), which is more flexible and is more wildly used than FFT, is applied to the blocker design. The method with filtering in DWT is very proper to design blocker in both 2-D and 3-D shapes. To verify the efficiency of this method, blockers of some models are designed and the results show that blocker design with DWT is effective fer the blocker designs

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Discovery of CPA`s Tacit Decision Knowledge Using Fuzzy Modeling

  • Li, Sheng-Tun;Shue, Li-Yen
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2001.01a
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    • pp.278-282
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    • 2001
  • The discovery of tacit knowledge from domain experts is one of the most exciting challenges in today\`s knowledge management. The nature of decision knowledge in determining the quality a firm\`s short-term liquidity is full of abstraction, ambiguity, and incompleteness, and presents a typical tacit knowledge extraction problem. In dealing with knowledge discovery of this nature, we propose a scheme that integrates both knowledge elicitation and knowledge discovery in the knowledge engineering processes. The knowledge elicitation component applies the Verbal Protocol Analysis to establish industrial cases as the basic knowledge data set. The knowledge discovery component then applies fuzzy clustering to the data set to build a fuzzy knowledge based system, which consists of a set of fuzzy rules representing the decision knowledge, and membership functions of each decision factor for verifying linguistic expression in the rules. The experimental results confirm that the proposed scheme can effectively discover the expert\`s tacit knowledge, and works as a feedback mechanism for human experts to fine-tune the conversion processes of converting tacit knowledge into implicit knowledge.

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Development of a Adaptive Knowledge Base Object Model for Intelligent Tutoring System (지능형 교육 시스템을 위한 적응적 지식베이스 객체 모형 개발)

  • Kim Yong-Beom;Kim Yung-Sik
    • The KIPS Transactions:PartB
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    • v.13B no.4 s.107
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    • pp.421-428
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    • 2006
  • Intelligent Tutoring System(ITS), which offers individualized learning environment that consider many learners' variable, is realized by the effective alternative to take the place of domain expert. Accordingly, research on Learning Companion System(LC) is currently noticing. However, to develop LCS which applies effective interaction, it is necessary to combine several LCs, and personalized knowledge base have to be made first. Therefore, in this paper, we propose the 'Knowledge Base Object Medel', which is based on connectionist' in cognition structure, represents learner's knowledge to self-learnig object, and grows adaptive object by proprietor, verify the validity. This model lays the groundwork for design of personalized knowledge base, offers clue to development of adaptive ITS using knowledge base object.

A Theoretical Study on the Knowledge-Based System for Design (디자인을 위한 지식기반시스템의 이론적 고찰)

  • 김태현
    • Korean Institute of Interior Design Journal
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    • no.7
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    • pp.70-78
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    • 1996
  • Artificial Intelligence is generally concerned with tasks whose execution appears to involve some intelligence if done by humans, and knowledge-based system ( in other word, expert system) is the research about the specific domain. This concept also can be applied to interior design field. So the purpose of this study is in reconstructing the accomplishment of artificial Intelligence and knowledge engineering, searching basic theories and cased to knowledge engineering , searching basic theories and cases to formulate knowledge -based design system, and testing the posibilities how the design information can be dealt in computer system. Given that recognition , two major problems must be solved before knowledge-based CAD systems could be come practical : Firstly , identification of the interior of designers use .Secondly , representing this knowledge in a computationally effective manner. I had discussed the basic concepts on which to base a knowledge- based design model, knowledge representation schemes, and problem solving, I could find the possibility which the knowledge-based system can be applied to the interior design according to this study. But there are non-deductive, often irrational and now easily computerized design process in interior design. Those are problems which are relevant to the machine learning and the creativity in design. So there should be a lot of research about the machine learning and the creatively in design in order to construct successfully intelligent knowledge-based design system.

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A Formal Specification of Fuzzy Object Inference Model (퍼지 객체 추론 모델의 정형화)

  • Yang, Jae-Dong;Yang, Hyung-Jeong
    • Journal of KIISE:Databases
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    • v.27 no.2
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    • pp.141-150
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    • 2000
  • There are three significant drawbacks in extant fuzzy rule-based expert system languages. First, they lack the functionality of composite object inference. Second, they do not support fuzzy reasoning semantically easy to understand and conceptually simple to use. Third, knowledge representation and reasoning style of their model have a great semantic gap with those of current database models. Therefore, it is very difficult for the two models to be seamlessly integrated with each other. This paper provides the formal specification of a fuzzy object inference model to solve the three drawbacks. GIS(Geographic Information System) application domain is used to demonstrate that our model naturally models complex GIS information in terms of composite objects and successfully performs fuzzy inference between them.

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Discovery of Interesting Knowlege using Concept Hierarchy (개념 계층 이용 흥미로운 부분 데이터의 탐색)

  • 홍정희;김성민;남도원;이동하;이전영
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2000.04a
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    • pp.261-270
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    • 2000
  • 개념 계층(Concept Hierarchy)은 데이터베이스 분야에서 사용되는 대표적인 배경 지식(Background Knowledge)으로써, 데이터베이스에 내재되어 있는 구조적인 정보, 데이터의 분포, 영역전문가(Domain Expert)에 의해 주어지는 외부 지식 등이 반영되어 있다. 개념 계층의 특성상 부모(parent)-자식(child) 관계가 있는 두 노드가 있을 때, 한 노드의 값으로부터 다른 노드의 값을 추정할 수 있다. 이 추정된 값을 기대치라고 하고, 한 노드의 값으로부터 추정된 기대치와 실제치가 상당히 상이한 값을 보이는 노드가 있을 때, 이를 흥미롭다(interesting)라고 할 수 있다. 그러나 아직까지 개념계층상에서의 흥미로운 부분 탐색에 대한 연구가 없었으며, 흥미로움(interestingness)의 척도(measurement)에 대한 연구로서는 신뢰도(confidence), 리프트(lift), 컨빅션(conviction)등이 있다. 그러나 이런 흥미도의 척도에 관한 연구도 연관규칙에 한정되어 이루어졌으므로 개념계층상의 데이터에 적용하기 위해서는 약간의 수정 및 새로운 정의가 필요하다. 본 논문에서는 데이터의 특성에 따른 개념계층이 존재할 때, 이를 이용하여 기대치와 실제치가 상이한 흥미로운 부분을 발견하고자 하며, 이를 위하여 개념계층이 존재할 때, 이를 이용하여 기대치와 실제치가 상이한 흥미로운 부분을 발견하고자 하며, 이를 위하여 개념계층상에서의 흥미도의 척도를 제안하고 흥미로운 부분을 탐색하는 방법을 기술하고자 한다. 또한 데이터마이닝의 결과인 연관규칙을 개념계층에 적용하여 연관규칙을 통해 얻어질 수 있는 기대치를, 지지도(support), 신뢰도(confidence), 리프트(lift), 컨빅션(conviction)등의 관계를 통해 다양한 방법으로 모색해본다. 이 연구에서 제안하는 이러한 개념계층상의 흥미로운 부분의 탐색은, 전자 상거래에서의 CRM(Customer Relationship Management)나 틈새시장(niche market) 마케팅 등에 적용가능하리라 여겨진다.

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Locomotive Scheduling Using Constraint Satisfaction Problems Programming Technique

  • Hwang, Jong-Gyu;Lee, Jong-Woo;Park, Yong-Jin
    • KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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    • v.4B no.1
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    • pp.29-35
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    • 2004
  • Locomotive scheduling in railway systems experiences many difficulties because of the complex interrelations among resources, knowledge and various constraints. Artificial intelligence technology has been applied to solve these scheduling problems. These technologies have proved to be efficient in representing knowledge and rules for complex scheduling problems. In this paper, we have applied the CSP (Constraints Satisfaction Problems) programming technique, one of the AI techniques, to solve the problems associated with locomotive scheduling. This method is more effective at solving complex scheduling problems than available mathematical programming techniques. The advanced locomotive scheduling system using the CSP programming technique is realized based on the actual timetable of the Saemaul type train on the Kyong-bu line. In this paper, an overview of the CSP programming technique is described, the modeling of domain and constraints is represented and the experimental results are compared with the real-world existing schedule. It is verified that the scheduling results by CSP programming are superior to existing scheduling performed by human experts. The executing time for locomotive scheduling is remarkably reduced to within several decade seconds, something requiring several days in the case of locomotive scheduling by human experts.

Development of Polynomial Based Response Surface Approximations Using Classifier Systems (분류시스템을 이용한 다항식기반 반응표면 근사화 모델링)

  • 이종수
    • Korean Journal of Computational Design and Engineering
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    • v.5 no.2
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    • pp.127-135
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    • 2000
  • Emergent computing paradigms such as genetic algorithms have found increased use in problems in engineering design. These computational tools have been shown to be applicable in the solution of generically difficult design optimization problems characterized by nonconvexities in the design space and the presence of discrete and integer design variables. Another aspect of these computational paradigms that have been lumped under the bread subject category of soft computing, is the domain of artificial intelligence, knowledge-based expert system, and machine learning. The paper explores a machine learning paradigm referred to as teaming classifier systems to construct the high-quality global function approximations between the design variables and a response function for subsequent use in design optimization. A classifier system is a machine teaming system which learns syntactically simple string rules, called classifiers for guiding the system's performance in an arbitrary environment. The capability of a learning classifier system facilitates the adaptive selection of the optimal number of training data according to the noise and multimodality in the design space of interest. The present study used the polynomial based response surface as global function approximation tools and showed its effectiveness in the improvement on the approximation performance.

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A Survey Study for the Operation of Site-Based Environmental Education Programs (체험환경교육 프로그램의 운영 실태에 관한 연구)

  • Park, Tae Yoon;Choi, Don-Hyung;Park, Hyun-Ju;Noh, Kyung-Im;Ko, Hee-Ryung
    • Journal of the Korean Society of Environmental Restoration Technology
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    • v.6 no.2
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    • pp.1-10
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    • 2003
  • The purpose of this study was to survey the status of the operation of site-based environmental education(EE) programs. This study surveyed 165 schools and organizations that operated site-based EE program in 2000 using a mail questionnaire and interviews. The response rate was 43%. The result indicated that awareness, participation, and attitude were considerably addressed, while knowledge and skills were addressed to a lesser degree. There were some difficulties in motivating students and in considering the developmental stage of participants. For programing the site-based EE, financial support and expert knowledge of EE were needed most of all. Learning materials for various and hand-on activities were also needed. The affective domain, such as awareness and attitude, showed marked improvement in the outcomes of the programs. Direct experience and sensitivity, connection with school education, regional characteristics were sufficiently addressed in the programs, while cultural aspects, fairness, originality, and accuracy were not. Flexibility in performing the programs and less rigidity of report on operations were needed. Through the discussion of the results, some improvements for the operation of site-based EE program were suggested.

Blocker Design of Closed Die Forging with Wavelet Transform (이산 웨이블릿 변환을 이용한 형단조 공정의 예비성형용 금형 설계)

  • 한상훈;임성한;오수익
    • Transactions of Materials Processing
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    • v.12 no.4
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    • pp.277-283
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    • 2003
  • In a closed-die forging process, blocker has been used to fill and distribute metal well in finisher die. Generally, the blocker shape was determined by an expert with many experiences. However, the manual blocker design process takes much time and efforts, so various automatic methods for the blocker design process have been suggested for the last three decades. The method with filtering in FFT (Fast Fourier Transform) for the blocker design provides general solution than other methods. But. due to the properties of FFT in time-frequency domain, this method has some drawbacks such as long calculation time, difficulty of local control and additional boundary process after filtering. In this study. DWT (Discrete Wavelet Transform), which is more flexible and is more wildly used than FFT, is applied to the blocker design. The method with filtering in DWT is very proper to design blocker in both 2-D and 3-D shapes. To verify the efficiency of this method, blockers of some models are designed and the results show that blocker design with DWT is effective for the blocker designs.