• 제목/요약/키워드: selection approach

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러프집합 이론을 이용한 러프 엔트로피 기반 지식감축 (Rough Entropy-based Knowledge Reduction using Rough Set Theory)

  • 박인규
    • 디지털융복합연구
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    • 제12권6호
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    • pp.223-229
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    • 2014
  • 대용량의 지식베이스 시스템에서 유용한 정보를 추출하여 효율적인 의사결정을 수행하기 위해서는 정제된 특징추출이 필수적이고 중요한 부분이다. 러프집합이론에 있어서 최적의 리덕트의 추출과 효율적인 객체의 분류에 대한 문제점을 극복하고 자, 본 연구에서는 조건 및 결정속성의 효율적인 특징추출을 위한 러프엔트로피 기반 퀵리덕트 알고리듬을 제안한다. 제안된 알고리듬에 의해 유용한 특징을 추출하기 위한 조건부 정보엔트로피를 정의하여 중요한 특징들을 분류하는 과정을 기술한다. 또한 본 연구의 적용사례로써 실제로 UCI의 5개의 데이터에 적용하여 특징을 추출하는 시뮬레이션을 통하여 본 연구의 모델링이 기존의 방법과 비교결과, 제안된 방법이 효율성이 있음을 보인다.

Prototype-based Classifier with Feature Selection and Its Design with Particle Swarm Optimization: Analysis and Comparative Studies

  • Park, Byoung-Jun;Oh, Sung-Kwun
    • Journal of Electrical Engineering and Technology
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    • 제7권2호
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    • pp.245-254
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    • 2012
  • In this study, we introduce a prototype-based classifier with feature selection that dwells upon the usage of a biologically inspired optimization technique of Particle Swarm Optimization (PSO). The design comprises two main phases. In the first phase, PSO selects P % of patterns to be treated as prototypes of c classes. During the second phase, the PSO is instrumental in the formation of a core set of features that constitute a collection of the most meaningful and highly discriminative coordinates of the original feature space. The proposed scheme of feature selection is developed in the wrapper mode with the performance evaluated with the aid of the nearest prototype classifier. The study offers a complete algorithmic framework and demonstrates the effectiveness (quality of solution) and efficiency (computing cost) of the approach when applied to a collection of selected data sets. We also include a comparative study which involves the usage of genetic algorithms (GAs). Numerical experiments show that a suitable selection of prototypes and a substantial reduction of the feature space could be accomplished and the classifier formed in this manner becomes characterized by low classification error. In addition, the advantage of the PSO is quantified in detail by running a number of experiments using Machine Learning datasets.

Bayesian Testing for the Shape Parameter of Gamma Distribution : An Encompassing Approach

  • Moon, Gyoung-Ae
    • Journal of the Korean Data and Information Science Society
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    • 제16권4호
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    • pp.861-870
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    • 2005
  • The Bayesian model selection procedures for the shape parameter of gamma distribution are proposed in order to test that the failure rate of gamma distribution is constant, increasing or decreasing. The encompassing intrinsic Bayes factor by Beger and Pericchi (1996) based on Jeffreys prior for shape parameter is used to investigate the usefulness of the proposed Bayesian model selection procedures via both real data and pseudo data.

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Selection Conditional on Associated Measurements

  • Yeo, Woon-Bang
    • Journal of the Korean Statistical Society
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    • 제12권2호
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    • pp.110-114
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    • 1983
  • In this paper, a random subset selection procedure for the choice of the k best objects out of n primary measurements $Y_t$ is considered when only the associated measurements $X_t$ are available. In contrast to Yeo and David (1992), where only the ranks of the X's are needed, the present uses the observed X-values. The approach is illustrated numerically when X and Y are bivariate normal and the standard deviation of X is known.

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출력궤환에 의한 PSS의 최적계수 선정에 관한 연구 (A Study on the Optimal Parameter Selection of PSS Using Output Feedback)

  • 박영문;이흥재;권태원
    • 대한전기학회논문지
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    • 제38권5호
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    • pp.337-342
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    • 1989
  • Since the late 1960s, the selection of the parameters of power system stabilizer (PSS) to damp out sustained low frequency oscillation of power generators in the steady state has been an active research area. This paper presents a new approach to select the optimal PSS parameters using the sensitivity of the quadratic performance with respect to the PSS parameters. The proposed algorithm has been applied to Seo-Cheon fossil power plant.

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Bayesian Variable Selection in the Proportional Hazard Model

  • Lee, Kyeong-Eun
    • Journal of the Korean Data and Information Science Society
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    • 제15권3호
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    • pp.605-616
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    • 2004
  • In this paper we consider the proportional hazard models for survival analysis in the microarray data. For a given vector of response values and gene expressions (covariates), we address the issue of how to reduce the dimension by selecting the significant genes. In our approach, rather than fixing the number of selected genes, we will assign a prior distribution to this number. To implement our methodology, we use a Markov Chain Monte Carlo (MCMC) method.

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신뢰성 이론을 이용한 자동창고 설비 선정 전문가 시스템 개발에 관한 연구 (Development of the Expert System for Selection of Equipment for Automated Warehouses Using Reliability Theory)

  • 이영해;정창식
    • Asia pacific journal of information systems
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    • 제8권3호
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    • pp.135-145
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    • 1998
  • There exists popular approach using certainty factor (CF) for the development of effective reasoning mechanism under uncertainty in Expert System, However, there is a problem with CF. The CF values could be resulted in the opposite of given conditional probabilities. In this paper, a method for, reasoning under uncertainty using reliability theory to overcome the problem is proposed. And the proposed method is used in the development of Expert System for the selection of equipment for automated warehouses.

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FMS의 최적구성에 따른 설비교체 시점의 결정 (A Determination of the Optimal Replace Time of Equipment in the FMS Design)

  • 이동춘;신현재
    • 산업경영시스템학회지
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    • 제14권24호
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    • pp.163-168
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    • 1991
  • In the FMS design, the important points are the selection of parts and the determination of configuration. The common approach method which solve the selection of parts are the determination of configuration has improved that the two points are simultaneously. This study finds the best method which parts combination and configuration are satisfied at the same time. And the optimal replace time of equipment under limited budget on the view Point of engineering. economy.

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Current status of the surgery-first approach (part I): concepts and orthodontic protocols

  • Choi, Dong-Soon;Garagiola, Umberto;Kim, Seong-Gon
    • Maxillofacial Plastic and Reconstructive Surgery
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    • 제41권
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    • pp.10.1-10.8
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    • 2019
  • The "surgery-first" approach, defined as a team approach between surgeons and orthodontists for orthognathic surgery without preoperative orthodontic treatment, is aimed at dental decompensation. A brief historical background and indications for the surgery-first approach are reviewed. Considering the complicated mechanism of postoperative orthodontic treatment, the proper selection of patients is a vital component of successful surgery-first approach.

A Hybrid Approach for the Morpho-Lexical Disambiguation of Arabic

  • Bousmaha, Kheira Zineb;Rahmouni, Mustapha Kamel;Kouninef, Belkacem;Hadrich, Lamia Belguith
    • Journal of Information Processing Systems
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    • 제12권3호
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    • pp.358-380
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    • 2016
  • In order to considerably reduce the ambiguity rate, we propose in this article a disambiguation approach that is based on the selection of the right diacritics at different analysis levels. This hybrid approach combines a linguistic approach with a multi-criteria decision one and could be considered as an alternative choice to solve the morpho-lexical ambiguity problem regardless of the diacritics rate of the processed text. As to its evaluation, we tried the disambiguation on the online Alkhalil morphological analyzer (the proposed approach can be used on any morphological analyzer of the Arabic language) and obtained encouraging results with an F-measure of more than 80%.