• 제목/요약/키워드: Incomplete Information

검색결과 558건 처리시간 0.028초

Evaluating Green Supply Chain Management with Incomplete Information

  • Tseng, Ming-Lang;Lin, Ru-Jen;Chiu, Anthony Shun Fung
    • Industrial Engineering and Management Systems
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    • 제11권2호
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    • pp.165-169
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    • 2012
  • There has been a growing interest in firms' environmental sustainability activities to improve environmental practices in their supply chain. This study aims to deal with supplier evaluation of firm's green supply chain management (GSCM) criteria with incomplete information. Nevertheless, the suitable supplier is a key strategic direction in eliminating environmental impact on supply chain management for manufacturing firms. The firm's GSCM criteria and supplier selection need to be unified as a system to improve the firm's performance.

Application of NORM to the Multiple Imputation for Multivariate Missing Data

  • 김현정;문승호;신재경
    • Journal of the Korean Data and Information Science Society
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    • 제13권2호
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    • pp.105-113
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    • 2002
  • The statistical analysis of incomplete data sometimes requires handling of incomplete observations. Towards this end, each case with some missing values generally should be deleted, namely, resulting in only use of non-missing cases. EM algorithm(Dempster et al., 1977) which involves prediction and estimation steps is a general method among others. In this article, we use the free software NORM developed for multiple imputation, which uses DA(Data Augmentation) algorithm in its imputation, and evaluate its efficiency through a numerical example.

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재공학 환경에서 적용성 향상을 위한 디자인 패턴의 UML 표현 (Design Pattern to Improve the Applicability In a Reengineering Environment Represented with UML)

  • 최성만;김송주;유철중;장옥배;이정열
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 2003년도 봄 학술발표논문집 Vol.30 No.1 (B)
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    • pp.148-150
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    • 2003
  • 본 논문은 재공학 환경에서 기존의 디자인 패턴을 적용성 향상을 위해 UML로 표현하였으며, 대상으로는 디자인 패턴 중에서 Strategy Pattern과 Visitor Pattern을 이용해 보았다. Strategy Pattern에서는{variation}과 {incomplete}를 이용하였다.{variation}은 메소드 구현시 패턴을 캡슐화하여 다양하게 변경될 수 있도록 하였다. 또한,{incomplete}는 주어진 관계를 만족하는 새로운 클래스가 패턴 인스턴스화 동안에 추가될 수 있도록 하였다. Visitor pattern에서의{extensible}은 클래스 인터페이스가 패턴을 캡슐화하고 있는 개념으로 다양하게 변경될 수 있도록 하였다. 즉, 클래스 인터페이스는 패턴 인스턴스화에 의존적이며 새로운 메소드와 속성을 클래스가 기능적으로 확장할 수 있는 기능을 갖는다.

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불완전정보 전력거래 해석을 위한 게임이론의 적용 (An Application of Game theory to Power Transactions under Incomplete Information)

  • 강동주;박만근;김발호;박종배
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2000년도 하계학술대회 논문집 A
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    • pp.19-21
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    • 2000
  • This paper presents a game theory application for analyzing power transactions and market design in a deregulated energy marketplace such as PoolCo. The conventional least-cost approaches for the generation resource schedule can not exactly handle recent real-world situations. A systematic tool using game theory for the market participants is presented such that it determines the net profits through the optimal bidding strategies including the strategies for the bidding prices and bidding generations. We treat this power transaction game as incomplete information one, which means each market participants does not know other's cost function. And the demand elasticity of the energy price is considered for the realistic modeling of the deregulated marketplace.

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AutoEncoder와 FCM을 이용한 불완전한 데이터의 군집화 (Clustering of Incomplete Data Using Autoencoder and fuzzy c-Means Algorithm)

  • 박동철;장병근
    • 한국통신학회논문지
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    • 제29권5C호
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    • pp.700-705
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    • 2004
  • Autoencoder와 Fuzzy c-Means 알고리즘을 이용하여, 불완전한 데이터의 군집화를 위한 알고리즘이 본 논문에서 제안되었다. 본 논문에서 제안된 Optimal Completion Autoencoder Fuzzy c-Means (OCAEFCM)은 손상되어 불완전한 데이터의 최적 복원과 데이터의 군집화를 위해 Autoencoder Neural Network (AENN) 과 Gradient-based FCM (GBFCM)을 이용하였다. OCAEFCM 의 성능평가를 위해 IRIS 데이터와 금융기관에서 취득한 실제 데이터를 사용하였다 기존의 Optimal Completion Strategy FCM (OCSFCM)과 비교했을 때, 제안된 OCAEFCM 이 OCSFCM 보다 18%-20%의 성능 향상을 보여준다.

경기주기와 베이지안 학습(Bayesian learning) 기법을 고려한 개인의 자산관리 연구 (Portfolio Management with the Business Cycle and Bayesian Learning)

  • 박세영;이현탁;이유나;장봉규
    • 한국경영과학회지
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    • 제39권2호
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    • pp.49-66
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    • 2014
  • This paper studies optimal consumption and investment behaviors of an individual when risky asset returns and her income are affected by the business cycle. The investor considers the incomplete information risk of unobservable macroeconomic conditions and updates her belief of expected risky asset returns through Bayesian learning. We find that the optimal investment strategy, certainty equivalent wealth, and portfolio hedging demand significantly depend on the belief about the macroeconomic conditions.

A Bayesian uncertainty analysis for nonignorable nonresponse in two-way contingency table

  • Woo, Namkyo;Kim, Dal Ho
    • Journal of the Korean Data and Information Science Society
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    • 제26권6호
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    • pp.1547-1555
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    • 2015
  • We study the problem of nonignorable nonresponse in a two-way contingency table and there may be one or two missing categories. We describe a nonignorable nonresponse model for the analysis of two-way categorical table. One approach to analyze these data is to construct several tables (one complete and the others incomplete). There are nonidentifiable parameters in incomplete tables. We describe a hierarchical Bayesian model to analyze two-way categorical data. We use a nonignorable nonresponse model with Bayesian uncertainty analysis by placing priors in nonidentifiable parameters instead of a sensitivity analysis for nonidentifiable parameters. To reduce the effects of nonidentifiable parameters, we project the parameters to a lower dimensional space and we allow the reduced set of parameters to share a common distribution. We use the griddy Gibbs sampler to fit our models and compute DIC and BPP for model diagnostics. We illustrate our method using data from NHANES III data to obtain the finite population proportions.

실시간 센서 네트워크에서 불완전 센서 스트림 데이터를 위한 질의 처리 시스템 (Query Processing System for Incomplete Sensor Stream Data of in Real-time Sensor Network)

  • 장유호;이상호;김용승;오염덕
    • 한국컴퓨터정보학회:학술대회논문집
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    • 한국컴퓨터정보학회 2014년도 제49차 동계학술대회논문집 22권1호
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    • pp.123-124
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    • 2014
  • 무선 센서 네트워크는 센서들을 근거리 네트워크로 연결하여 사용자와 현장의 정보를 실시간으로 연결해 주는 매개체 역할을 한다. 이러한 무선 센서 네트워크는 기존의 컴퓨팅 시스템과는 달리 제한된 자원과 환경 속에서 동작을 해야 하고, 접근이 힘든 곳이나 지속적인 관리가 필요한 지역에서 효율적으로 사용된다. 본 논문에서는 무선 센서네트워크의 제한된 자원 속에서 불완전 스트림 데이터를 효율적으로 정제하고 처리하여 빠르고 정확한 질의어 처리가 가능한 질의 시스템을 제안하였다.

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Analysis of recurrent event data with incomplete observation gaps using piecewise models

  • Kim, Yang-Jin
    • Journal of the Korean Data and Information Science Society
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    • 제25권5호
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    • pp.1117-1125
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    • 2014
  • In a longitudinal study, subjects can experience same type of events repeatedly. Also, there may exist intermittent dropouts resulting in repeated observation gaps during which no recurrent events are observed. Furthermore, when such observation gaps have incomplete forms caused by the unknown termination times of observation gaps, ordinary approaches result in biased estimates. In this study, we investigate the effect of ignoring observation gaps and propose methods to overcome this problem. For estimating the distribution of unknown termination times, an interval-censored mechanism is applied and two cases are considered. Simulation studies are carried out to evaluate the performance of the proposed method. Conviction data of young drivers with several suspensions are analyzed to illustrate the suggested approach.

Development of Neural network based Plasma Monitoring System and simulator for Laser Welding Quality Analysis

  • Kwon, Jang-Woo;Son, Joong-Soo;Lee, Myung-Soo;Lee, Kyung-Don
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 1999년도 추계종합학술대회
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    • pp.494-497
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    • 1999
  • Neural networks are shown to be effective in being able to distinguish incomplete penetration-like weld defects by directly analyzing the plasma which is generated on each impingement of the laser on the materials. The performance is similar to that of existing methods based on extracted feature parameters. In each case around 93% of the defects in a database derived from 100 artificially produced defects of known types can be placed into one of two classes: incomplete penetration and bubbling. Especially we present simulator for weld defects classification and data analysis. The present method based on classification using plasma is faster, and the speed is sufficient to allow on-line classification during data collection.

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