• Title/Summary/Keyword: Model Matching

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Statistical Matching Techniques Using the Robust Regression Model (로버스트 회귀모형을 이용한 자료결합방법)

  • Jhun, Myoung-Shic;Jung, Ji-Song;Park, Hye-Jin
    • The Korean Journal of Applied Statistics
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    • v.21 no.6
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    • pp.981-996
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    • 2008
  • Statistical matching techniques whose aim is to achieve a complete data file from different sources. Since the statistical matching method proposed by Rubin (1986) assumes the multivariate normality for data, using this method to data which violates the assumption would involve some problems. This research proposed the statistical matching method using robust regression as an alternative to the linear regression. Furthermore, we carried out a simulation study to compare the performance of the robust regression model and the linear regression model for the statistical matching.

A DC Motor Speed Control by Selection of PID Parameter using Genetic Algorithm

  • Yoo, Heui-Han;Lee, Yun-Hyung
    • Journal of Advanced Marine Engineering and Technology
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    • v.31 no.3
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    • pp.293-300
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    • 2007
  • The aim of this paper is to design a speed controller of a DC motor by selection of a PID parameters using genetic algorithm. The model of a DC motor is considered as a typical non-oscillatory, second-order system, And this paper compares three kinds of tuning methods of parameter for PID controller. One is the controller design by the genetic algorithm. second is the controller design by the model matching method third is the controller design by Ziegler and Nichols method. It was found that the proposed PID parameters adjustment by the genetic algorithm is better than the Ziegler & Nickels' method. And also found that the results of the method by the genetic algorithm is nearly same as the model matching method which is analytical method. The proposed method could be applied to the higher order system which is not easy to use the model matching method.

State Feedback Control of Asynchronous Sequential Machines with Uncontrollable Inputs: Application to Error Counters (제어 불능 입력이 존재하는 비동기 순차 머신의 상태 피드백 제어 및 오류 카운터로의 응용)

  • Yang, Jung-Min;Kwak, Seong-Woo
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.10
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    • pp.967-973
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    • 2009
  • The model matching problem of asynchronous sequential machines is to design a corrective controller such that the stable-state behavior of the closed-loop system matches that of a prescribed model. In this paper, we address model matching when the external input set consists of controllable inputs and uncontrollable ones. Like in the frame of supervisory control of Discrete-Event Systems (DES), uncontrollable inputs cannot be disabled and must be transmitted to the plant without any change. We postulate necessary and sufficient conditions for the existence of a corrective controller that solves model matching despite the influence of uncontrollable events. Whenever a controller exists, the algorithm for its design is outlined. To illustrate the physical meaning of the proposed problem, the closed-loop system of an asynchronous machine with the proposed control scheme is implemented in VHDL code.

Rational function model-based image matching for digital elevation model

  • PARK CHOUNG-HWAN
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2005.11a
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    • pp.59-80
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    • 2005
  • This Paper Presents a Rational Function Model (RFM)-based image matching technique for IKONOS satellite imagery. This algorithm adopts the object-space approach and reduces the search space within the confined line-shaped area called the Piecewise Matching Line (PLM). Also, the detailed procedure of generating 3-D surface information using the Rational Function model Coefficients (RFCs) is introduced as an end-user point of view. As a result, the final generated Digital Elevation Model (DEM) using the proposed scheme shows a mean error of 2$\cdot$2 m and RMSE of 3$\cdot$8 m compared with that from 1:5000 digital map.

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Development of Noninformative Priors in the Burr Model

  • Cho, Jang-Sik;Kang, Sang-Gil;Baek, Sung-Uk
    • Journal of the Korean Data and Information Science Society
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    • v.14 no.1
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    • pp.83-92
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    • 2003
  • In this paper, we derive noninformative priors for the ratio of parameters in the Burr model. We obtain Jeffreys' prior, reference prior and second order probability matching prior. Also we prove that the noninformative prior matches the alternative coverage probabilities and a HPD matching prior up to the second order, respectively. Finally, we provide simulated frequentist coverage probabilities under the derived noninformative priors for small and moderate size of samples.

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On Second Order Probability Matching Criterion in the One-Way Random Effect Model

  • Kim, Dal Ho;Kang, Sang Gil;Lee, Woo Dong
    • Communications for Statistical Applications and Methods
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    • v.8 no.1
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    • pp.29-37
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    • 2001
  • In this paper, we consider the second order probability matching criterion for the ratio of the variance components under the one-way random effect model. It turns out that among all of the reference priors given in Ye(1994), the only one reference prior satisfies the second order matching criterion. Similar results are also obtained for the intraclass correlation as well.

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Artificial Neural Network-based Weight Factor Determination Method for the Enhanced XML Schema Matching of Bridge Engineering Documents (교량 건설 문서의 강화된 XML 스키마 매칭을 위한 인공신경망 기반의 요소 가중치 선정 방안)

  • Park, Sang I.;Kwon, Tae-Ho;Park, Junwon;Seo, Kyung-Wan;Yoon, Young-Cheol
    • Journal of the Korean Society of Safety
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    • v.37 no.1
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    • pp.41-48
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    • 2022
  • Bridge engineering documents have essential contents that must be referenced continuously throughout a structure's entire life cycle, but research related to the quality of the contents is still lacking. XML schema matching is an excellent technique to improve the quality of stored data; however, it takes excessive computing time when applied to documents with many contents and a deep hierarchical structure, such as bridge engineering documents. Moreover, it requires a manual parametric study for matching elements' weight factors, maintaining a high matching accuracy. This study proposes an efficient weight-factor determination method based on an artificial neural network (ANN) model using the simplified XML schema-matching method proposed in a previous research to reduce the computing time. The ANN model was generated and verified using 580 data of document properties, weight factors, and matching accuracy. The proposed ANN-based schema-matching method showed superiority in terms of accuracy and efficiency compared with the previous study on XML schema matching for bridge engineering documents.

Model Order Reduction Using Moment-Matching Method Based on Krylov Subspace and Its Application to FRF Calculation for Array-Type MEMS Resonators (Krylov 부공간에 근거한 모멘트일치법을 이용한 모델차수축소법 및 배열형 MEMS 공진기 주파수응답함수 계산에의 응용)

  • Han, Jeong-Sam;Ko, Jin-Hwan
    • Proceedings of the KSME Conference
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    • 2008.11a
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    • pp.436-441
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    • 2008
  • One of important factors in designing array-type MEMS resonators is obtaining a desired frequency response function (FRF) within a specific range. In this paper Krylov subspace-based model order reduction using moment-matching with non-zero expansion points is represented to calculate the FRF of array-type resonators. By matching moments at a frequency around a specific range of the array-type resonators, required FRFs can be efficiently calculated with significantly reduced systems regardless of their operating frequencies. In addition, because of the characteristics of moment-matching method, a minimal order of reduced system with a specified accuracy can be determined through an error indicator using successive reduced models, which is very useful to automate the order reduction process and FRF calculation for structural optimization iterations.

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Partial Model Matching Control System Design by Considering Pole-Placements (극배치를 고려한 제분 Model Matching 제어계 설계)

  • 이수흠;김수중
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.35 no.10
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    • pp.427-437
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    • 1986
  • Identification of the plants is not easy task especially in the fields of process control. From this point of view, Kitamori developed a method of control system design based on partial knowledge about controlled processes. However, it is difficult to control the oscillatory plant by kitamori's method. In this paper, we develope a method of partial model matching control system design, which have desirable pole-placements in order to improve the above defects. Design examples are given to illustrate the effectiveness of the method.

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Reference Priors in a Two-Way Mixed-Effects Analysis of Variance Model

  • Chang, In-Hong;Kim, Byung-Hwee
    • Journal of the Korean Data and Information Science Society
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    • v.13 no.2
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    • pp.317-328
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    • 2002
  • We first derive group ordering reference priors in a two-way mixed-effects analysis of variance (ANOVA) model. We show that posterior distributions are proper and provide marginal posterior distributions under reference priors. We also examine whether the reference priors satisfy the probability matching criterion. Finally, the reference prior satisfying the probability matching criterion is shown to be good in the sense of frequentist coverage probability of the posterior quantile.

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