• Title/Summary/Keyword: Machine knowledge

검색결과 643건 처리시간 0.029초

모의실험을 통한 전문가 시스템 (A Simulation-Based Expert System Paradigm)

  • 김선욱
    • 대한산업공학회지
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    • 제18권2호
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    • pp.99-107
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    • 1992
  • Both simulation and expert systems are popular ways to solve complex and hard problems. However, the results of the simulation, which include a large amount of valuable information as a good knowledge source, are not used efficiently. Furthermore, the development of the expert systems can fail because there is no expert or an expert is not available. A new Simulation-Based Expert System(SIMBES) paradigm has been constructed to overcome these problems. It consists of simulator, feature extractor, machine learning system, performance evaluator and Knowledge-Based Expert System(KBES). A SIMBES was implemented for an existing schedule-based MRP system in Smalltalk/V to show how this paradigm works and experimented for a large number of jobs. The KBES and the existing system produced better schedules for 72 percent and 28 percent of the jobs, respectively.

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FMS 일정계획 수립을 위한 지식기반 시스템 개발에 대한 연구 (Development of a Knowledge-Based System to Establish FMS Scheduling)

  • 최영민;오병완;김진용;이진규
    • 품질경영학회지
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    • 제22권3호
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    • pp.161-178
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    • 1994
  • FMS are being installed to improve productivity, manufacturing consistency and flexibility. However, FMS are quite expensive and efforts must be made to avoid the high investment risk. The objective of this paper is to enable the real-time rescheduling under dynamic changes in FMS environment. For this purpose, a KBSS (Knowledge-Based Scheduling System) in FMS environment is developed. This KBSS will meet various requirements of users, for example, to minimize makespan, average flow time, or to maximize machine utilization.

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Building a Model(s) to Examine the Interdependency of Content Knowledge and Reasoning as Resources for Learning

  • Cikmaz, Ali;Hwang, Jihyun;Hand, Brian
    • 한국수학교육학회지시리즈D:수학교육연구
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    • 제25권2호
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    • pp.135-158
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    • 2022
  • This study aimed to building models to understand the relationships between reasoning resources and content knowledge. We applied Support Vector Machine and linear models to the data including fifth graders' scores in the Cornel Critical Thinking Test and the Iowa Assessments, demographic information, and learning science approach (a student-centered approach to learning called the Science Writing Heuristic [SWH] or traditional). The SWH model showing the relationships between critical thinking domains and academic achievement at grade 5 was developed, and its validity was tested across different learning environments. We also evaluated the stability of the model by applying the SWH models to the data of the grade levels. The findings can help mathematics educators understand how critical thinking and achievement relate to each other. Furthermore, the findings suggested that reasoning in mathematics classrooms can promote performance on standardized tests.

A Methodology of Automated Analysis and Qualitative Assessment of Legislation and Court Decisions

  • Trofimov, Egor;Metsker, Oleg;Kopanitsa, Georgy
    • International Journal of Computer Science & Network Security
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    • 제22권11호
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    • pp.229-235
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    • 2022
  • This study aims to substantiate an interdisciplinary methodology for automated analysis and qualitative assessment of legislation and court decisions. The development of this kind of methodology will make it possible to fill a number of methodological gaps in various research areas, including law effectiveness assessment and legal monitoring. We have defined a methodology based on the interdisciplinary principles and tools. In general, it should be noted that even at the level of qualitative assessment made with the use of the methodology described above, the accumulation of knowledge about the relationship between legal objectives, indicators and computer methods of their identification can reduce the role of expert knowledge and subjective factor in the process of assessment, planning, forecasting and control over the state of legislation and law enforcement. Automation of intellectual processes becomes inevitable in a digital society, but, releasing experts from routine work, simultaneously reorients it to development of interdisciplinary methods and control over their application.

Simulated Annealing을 이용한 제약 네트워크에서의 제약 충족 방식에 관한 연구 (Constraint satisfaction algorithm in constraint network using simulated annealing method)

  • 차주헌;이인호;김재정
    • 한국정밀공학회지
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    • 제14권9호
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    • pp.116-123
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    • 1997
  • We have already presented the constraint satisfaction algorithm which could solve the closed loop porblem in constraint network by using local constraint propagation, variable elimination and constraint modularization. With this algorithm, we have implemented a knowledge-based system (intelligent CAD) for supporting machine design interactively. In this paper, we present newer constraint satisfaction algorithm which can solve inequalities or under-constrained problems in constraint network, interactively and effi- ciently. This algorithm is a hybrid type of using both declarative description (constraint representation) and optimization algorithm (Simulated Annealing), simultaneously. The under-constrained problems are represented by constraint networks and satisfied completely with this algorithm. The usefulness of our algorithm will be illustrated by the application to a gear design.

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Data-driven Value-enhancing Strategies: How to Increase Firm Value Using Data Science

  • Hyoung-Goo Kang;Ga-Young Jang;Moonkyung Choi
    • Asia pacific journal of information systems
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    • 제32권3호
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    • pp.477-495
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    • 2022
  • This paper proposes how to design and implement data-driven strategies by investigating how a firm can increase its value using data science. Drawing on prior studies on architectural innovation, a behavioral theory of the firm, and the knowledge-based view of the firm as well as the analysis of field observations, the paper shows how data science is abused in dealing with meso-level data while it is underused in using macro-level and alternative data to accomplish machine-human teaming and risk management. The implications help us understand why some firms are better at drawing value from intangibles such as data, data-science capabilities, and routines and how to evaluate such capabilities.

진화연산을 통해 만들어지는 토픽맵 (Evolutionary Topic Maps)

  • 김주호;홍원욱
    • 한국HCI학회:학술대회논문집
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    • 한국HCI학회 2009년도 학술대회
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    • pp.685-689
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    • 2009
  • 진화연산은 최적화와 기계학습에 널리 사용되지만 또한 창조적이고 새로운 것을 만드는 데에도 사용될 수 있다. 본 논문에서는 지식을 표현하는 유연한 구조인 토픽맵에 주목하여, 새롭고 창의적인 토픽맵을 생성하는 토픽맵의 진화 시스템을 제안한다. 여기서는 만들어진 토픽맵이 유효한지에 대한 사람의 평가를 활용하는 대화형 진화 연산 방법(Interactive Evolutionary Computation)이 사용된다. 본 진화하는 토픽맵 시스템은 창의성을 도모하는 도구로서, 사용자들에게 새롭고 창의적인 지식을 떠올릴 수 있도록 도울 수 있을 것이다. 앞으로는 이 시스템에 보다 토픽맵에 정교한 사용자 인터페이스와 시각화 방법을 도입하고 기계학습을 활용하여 시스템의 진화 중에 나타나는 사용자의 피로를 크게 줄이는 방법을 연구할 것이다.

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Approximate k values using Repulsive Force without Domain Knowledge in k-means

  • Kim, Jung-Jae;Ryu, Minwoo;Cha, Si-Ho
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제14권3호
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    • pp.976-990
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    • 2020
  • The k-means algorithm is widely used in academia and industry due to easy and simple implementation, enabling fast learning for complex datasets. However, k-means struggles to classify datasets without prior knowledge of specific domains. We proposed the repulsive k-means (RK-means) algorithm in a previous study to improve the k-means algorithm, using the repulsive force concept, which allows deleting unnecessary cluster centroids. Accordingly, the RK-means enables to classifying of a dataset without domain knowledge. However, three main problems remain. The RK-means algorithm includes a cluster repulsive force offset, for clusters confined in other clusters, which can cause cluster locking; we were unable to prove RK-means provided optimal convergence in the previous study; and RK-means shown better performance only normalize term and weight. Therefore, this paper proposes the advanced RK-means (ARK-means) algorithm to resolve the RK-means problems. We establish an initialization strategy for deploying cluster centroids and define a metric for the ARK-means algorithm. Finally, we redefine the mass and normalize terms to close to the general dataset. We show ARK-means feasibility experimentally using blob and iris datasets. Experiment results verify the proposed ARK-means algorithm provides better performance than k-means, k'-means, and RK-means.

클러스터 형성을 위한 지식 집약적 IT 부품 연구개발정책의 Dilemma : 공작기계제어 컴퓨터 사례 (The Formation of the Machine Tool Cluster and The Accumlation of Technological Capability of the Numerical Controller Industry in Korea)

  • 임채성
    • 기술경영경제학회:학술대회논문집
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    • 기술경영경제학회 2000년도 제17회 하계학술발표회 논문집
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    • pp.47-64
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    • 2000
  • This paper analyses characteristics of the numerical controller industry in market formation and the Flow of information between users and producers and the characteristic of knowledge base of the industry and discusses the difficulties derived, from the characteristics, in accumulation of technological capability In market formation betweenusers and producers, the multi-layered market is not favorable to domestic producers in that lower end market is not large enough to provide cardle market to them which produce inferior quality and lower price than importer products. The credibility of the permance of a product is difficult to prove until a critical mass of products are sold. Therefore gaining market share is deterred by unproven credibility of the performance of the product. The flow of information between users and producers is limited. The flow of information on users environment through mass market to producers is essential for improving credibility of a product. The nature of knowledge base is tacit and the means of knowledge transmission is limited. Technological licensing and reverse engineering, Which have been conventional industry. These characteristics provide conditions of vicious circle in accumulation of technological capability of the numerical controller industry. This paper argues that these characteristics of the industry challenges existing approach to R&D management and framework of science and technology policy.

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언어자원 자동 구축을 위한 위키피디아 콘텐츠 활용 방안 연구 (A Study on Utilization of Wikipedia Contents for Automatic Construction of Linguistic Resources)

  • 류철중;김용;윤보현
    • 디지털융복합연구
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    • 제13권5호
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    • pp.187-194
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    • 2015
  • 급변하는 자연언어를 기계가 이해할 수 있도록 하기 위해서는 다양한 언어지식자원(linguistic knowledge resources)의 구축이 필수적으로 수반된다. 본 논문에서는 온라인 콘텐츠의 특성을 활용해 언어지식자원을 자동으로 구축함으로써 지속적으로 확장 가능한 방법을 고안하고자 한다. 특히 언어분석 과정에서 가장 활용도가 높은 개체명(NE: Named Entity) 사전을 자동으로 구축, 확장하는데 주안점을 둔다. 이를 위해 본 논문에서는 개체명 사전 구축대상문서로 위키피디아(Wikipedia)를 선정, 그 특성을 파악하기 위해 다양한 통계 분석을 수행하였다. 이에 기반하여 위키피디아 콘텐츠가 갖는 구문적 특성과 구조 정보 등의 메타데이터를 활용하여 개체명 사전을 구축, 확장하는 방법을 제안한다.