• 제목/요약/키워드: Inference models

검색결과 449건 처리시간 0.028초

The restricted maximum likelihood estimation of a censored regression model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • 제24권3호
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    • pp.291-301
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    • 2017
  • It is well known in a small sample that the maximum likelihood (ML) approach for variance components in the general linear model yields estimates that are biased downward. The ML estimate of residual variance tends to be downwardly biased. The underestimation of residual variance, which has implications for the estimation of marginal effects and asymptotic standard error of estimates, seems to be more serious in some limited dependent variable models, as shown by some researchers. An alternative frequentist's approach may be restricted or residual maximum likelihood (REML), which accounts for the loss in degrees of freedom and gives an unbiased estimate of residual variance. In this situation, the REML estimator is derived in a censored regression model. A small sample the REML is shown to provide proper inference on regression coefficients.

Extracting Features of Human Knowledge Systems for Active Knowledge Management Systems

  • Yuan Miao;Robert Gay;Siew, Chee-Kheong;Shen, Zhi-Qi
    • 한국지능정보시스템학회:학술대회논문집
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    • 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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    • pp.265-271
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    • 2001
  • It is highly for the research in artificial intelligence area to be able to manage knowledge as human beings do. One of the fantastic natures that human knowledge management systems have is being active. Human beings actively manage their knowledge, solve conflicts and make inference. It makes a major difference from artificial intelligent systems. This paper focuses on the discussion of the features of that human knowledge systems, which underlies the active nature. With the features extracted, further research can be done to construct a suitable infrastructure to facilitate these features to build a man-made active knowledge management system. This paper proposed 10 features that human beings follow to maintain their knowledge. We believe it will advance the evolution of active knowledge management systems by realizing these features with suitable knowledge representation/decision models and software agent technology.

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On a Bayesian Estimation of Multivariate Regression Models with Constrained Coefficient Matrix

  • Kim, Hea-Jung
    • 품질경영학회지
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    • 제26권4호
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    • pp.151-165
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    • 1998
  • Consider the linear multivariate regression model $Y=X_1B_1+X_2B_2+U$, where Vec(U)~N(0, $\sum \bigotimes I_N$). This paper is concerned with Bayes infreence of the model when it is suspected that the elements of $B_2$ are constrained in the form of intervals. The use of the Gibbs sampler as a method for calculating Bayesian marginal posterior desnities of the parameters under a generalized conjugate prior is developed. It is shown that the a, pp.oach is straightforward to specify distributionally and to implement computationally, with output readily adopted for required inference summaries. The method developed is a, pp.ied to a real problem.

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탐색결과에 근거한 자연어질의 자동확장 및 응용에 관한 연구 고찰 (The Pragmatics of Automatic Query Expansion Based on Search Results of Natural Language Queries)

  • 노정순
    • 정보관리학회지
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    • 제16권2호
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    • pp.49-80
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    • 1999
  • 본 연구는 자연어 비불리언 탐색에서 탐색결과에 근거하여 질의를 수정, 확장, 결합하여 검색효과를 향상시키는 시스템들을 개념모델별로 성능을 고찰하고, 성능에 영향을 끼치는 요소들을 분석하여, 이론적인 개념의 틀을 제시하였다. 용어의 가중치기법, 문헌의 순위화방법, 용어선정알고리즘, 질의확장에 사용된 문헌수와 용어수, 적합성판정정보의 출처 및 척도, 배움표본의 크기, 부적합문헌정보의 사용여부, 용어확장방법, 질의의 크기, DB의 종류와 크기 등에 의해 영향을 받는 것으로 분석되었다.

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Emotion Modeling for Emotion-based Personalization Service

  • Kim, Tae Yeun;Bae, Sang Hyun
    • 통합자연과학논문집
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    • 제13권3호
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    • pp.97-104
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    • 2020
  • This study suggests the emotion space modeling and emotion inference methods suitable for personalized services based on psychological and emotional models. For personalized emotion space modeling taking into account the subjective disposition based on the empirical assessment of the personal emotions felt by the personalization process of emotion space was used as a decision support tool, the Analytic Hierarchy Process. This confirmed that the special learning to perform personalized emotion space modeling without considering the subjective tendencies. In particular to check the possible reasoning based on fuzzy emotion space modeling and sensitivity for the quantification and vague human emotion to it based on the inherent human sensitivity.

Clustering-based identification for the prediction of splitting tensile strength of concrete

  • Tutmez, Bulent
    • Computers and Concrete
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    • 제6권2호
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    • pp.155-165
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    • 2009
  • Splitting tensile strength (STS) of high-performance concrete (HPC) is one of the important mechanical properties for structural design. This property is related to compressive strength (CS), water/binder (W/B) ratio and concrete age. This paper presents a clustering-based fuzzy model for the prediction of STS based on the CS and (W/B) at a fixed age (28 days). The data driven fuzzy model consists of three main steps: fuzzy clustering, inference system, and prediction. The system can be analyzed directly by the model from measured data. The performance evaluations showed that the fuzzy model is more accurate than the other prediction models concerned.

Fault Diagnostic System Based on Fuzzy Time Cognitive Map

  • Lee, Kee-Sang;Kim, Sung-Ho
    • Transactions on Control, Automation and Systems Engineering
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    • 제1권1호
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    • pp.62-68
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    • 1999
  • FCM(Fuzzy Cognitive Map) is proposed for representing causal reasoning. Its structure allows systematic causal reasoning through a forward inference. Authors have already proposed a diagnostic system based on FCM to utilized to identify the true origin of fault by on-line pattern diagnosis. In FCM based fault diagnosis, Temporal Associative Memories (TAM) recall of FCM is utilized to identify the true origin of fault by on-line pattern match where predicted pattern sequences obtained from TAM recall of fault FCM models are compared with actually observed ones. In engineering processes, the propagation delays are induced by the dynamics of processes and may vary with variables involved. However, disregarding such propagation delays in FCM-based fault diagnosis may lead to erroneous diagnostic results. To solve the problem, a concept of FTCM(Fuzzy Time Cognitive Map) is introduced into FCM-based fault diagnosis in this work. Expecially, translation method of FTCM makes it possible to diagnose the fault for some discrete time. Simulation studies through two-tank system is carried out to verify the effectiveness of the proposed diagnostic scheme.

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뉴로 퍼지를 이용한 냉동기 성능 진단 기법 (Neuro-Fuzzy Diagnostic Technique for Performance Evaluation of a Chiller)

  • 신영기;장영수;김영일
    • 대한기계학회논문집B
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    • 제27권5호
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    • pp.553-560
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    • 2003
  • On-site diagnosis of chiller performance is an essential step fur energy saving business. The main purpose of the on-site diagnosis is to predict the COP of a target chiller. Many models based on thermodynamics background have been proposed for this purpose. However, they have to be modified from chiller to chiller and require deep insight into thermodynamics that most of field engineers are often lacking in. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). Quality of the training data for ANFIS, sampled over June through September, is assessed by checking COP prediction errors. The architecture of the ANFIS, its error bounds, and collection of training data are described in detail.

냉동기 성능 진단을 위한 적응형 뉴로퍼지(ANFIS) 모델 개발 (Prediction of Vapor-Compressed Chiller Performance Using ANFIS Model)

  • 신영기;장영수;김영일
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2001년도 추계학술대회논문집B
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    • pp.89-95
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    • 2001
  • On-site diagnosis of chiller performance is an essential step for energy saving business. The main purpose of the on-site diagnosis is to predict the COP of a target chiller. Many models based on thermodynamics background have been proposed for the purpose. However, they have to be modified from chiller to chiller and require deep insight into thermodynamics that most of field engineers are often lacking in. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). Quality of the training data for ANFIS, sampled over June through September, is assessed by checking COP prediction errors. The architecture of the ANFIS, its error bounds, and collection of training data are described in detail.

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Stability Analysis of Fuzzy-Model-Based Controller by Piecewise Quadratic

  • Wook Chang;Joo, Young-Hoon;Park, Jin-Bae
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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    • pp.169-172
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    • 1999
  • In this paper, piecewise quadratic Lyapunov functions are used to analyze the stability of fuzzy-model-based controller. We represent the nonlinear system using a Takagi-Sugeno fuzzy model, which represent the given nonlinear system by fuzzy inference rules and local linear dynamic models. The proposed stability analysis technique is developed by dividing the whole fuzzy system into the smaller separate fuzry systems to reduce the conservatism. Some necessary and sufficient conditions for the proposed method are obtained. Finally, stability of the closed system with various kinds of controller for TS fuzzy model is checked through the proposed method.

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