• 한국안전학회지
• /
• 제9권4호
• /
• pp.42-48
• /
• 1994

A rotor flux error-based approach for correcting the rotor time constant estimation used in the slip frequency calculator of indirect field oriented controller is presented in this paper. The controller was derived from the d-q induction machine model. Slip frequency gain is dependent on the machine parameter errors. And parameter errors result in rotor flux error. Thus, estimated rotor flux is compared to commanded rotor flux. The error between them is used for the estimation of rotor time constant. Simulation results which demonstrate the performance of this approach are presented.

• 한국신뢰성학회지:신뢰성응용연구
• /
• 제3권2호
• /
• pp.127-136
• /
• 2003

This paper investigates the effect of individual observations in regression models with MA(1) errors through the 'hat matrix' It shows that the first observation has the largest hat matrix diagonal component for $\theta$＜0 in the regression model with an intercept. This provides additional evidence for retaining the first observation in performing estimation in this setting. When the regression model goes to the origin and the independent variable has a deterministic trend, the last observation has the greatest leverage for │$\theta$│＜1 and may have potentially large impact on parameter estimation.

• 한국정보전자통신기술학회논문지
• /
• 제6권3호
• /
• pp.148-151
• /
• 2013

모델 오차 효과 및 민감도 분석을 사용하여 도래 방향 추정의 새로운 방법을 제시한다. 원하는 신호가 모델 오차 교정 효과를 통해 간섭을 제거한 후 얻어지게 되므로 추정에 있어서 채널 간섭 영향이 크게 줄어들게 된다. 모의실험을 통해 본 연구에서 제안된 방법이 기존의 방법에 비해 분해능과 정확성 추정이 향상되었음을 입증하였다.

• 대한인간공학회지
• /
• 제22권4호
• /
• pp.59-78
• /
• 2003

Most regression models of anthropometric variables use stature and/or weight as regressors; however, these 'flat' regression models result in large errors for anthropometric variables having low correlations with the regressors. To develop more accurate regression models for anthropometric variables, this study proposed a method to estimate anthropometric variables in a hierarchical manner based on the relationships among the variables and a process to develop and improve corresponding regression models. By applying the proposed approach, a hierarchical estimation structure was constructed for 59 anthropometric variables selected for the occupant package design of a passenger car and corresponding regression models were developed with the 1988 US Army anthropometric survey data. The hierarchical regression models were compared with the corresponding flat regression models in terms of accuracy. As results, the standard errors of the hierarchical regression models decreased by 28% (4.3mm) on average compared with those of the flat models.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.69.1-69
• /
• 2001

In this paper, observability properties of a multiantenna GPS measurement system for the estimation of errors in INS are presented. It is shown that time-invariant INS error models are observable with measurements from at least three GPS antennas on the vehicle. There is at least one unobservable mode with two antennas. There are three unobservable modes with one antenna. It is also shown that time-varying INS error models are instantaneously observable with measurements from three GPS antennas. A numerical simulation results are given to verify the effectiveness of the multiantenna measurement system on the INS error estimation. In the simulation, a GPS measurement system is considered in which a trade-off between computational load and accuracy of estimation is achieved.

• 경영과학
• /
• 제19권1호
• /
• pp.117-128
• /
• 2002

In this Paper we investigate the performance of the five efficiency estimation methods which include the stochastic frontier model estimated by maximum likelihood (SFML), the stochastic frontier model estimated by corrected ordinary least squares (SFCOLS), the data envelopment analysis (DIA) model, the combined estimation of SFML and DEA (SFML + DEA), and the combined estimation of SFCOLS arid DIA (SFCOLS+ DEA) using Monte Carlo analysis. The results include: 1) SFML provides most accurate efficiency estimates for the sample sloe 150 or over,2) SFML+DEAor SFCOLS + DIA Perform better for the cases with sample sloe 25, 50, and low random errors, 3) SFCOLS performs better for the close with sample sloe 25, 50, and very high random errors.

• Journal of the Korean Data and Information Science Society
• /
• 제16권4호
• /
• pp.1079-1086
• /
• 2005

Most discussions of single imputation methods and the EM algorithm concern point estimation of population quantities with missing values. A second concern is how to get standard errors of the point estimates obtained from the filled-in data by single imputation methods and EM algorithm. Now we focus on how to estimate standard errors with incorporating the additional uncertainty due to nonresponse. There are some approaches to account for the additional uncertainty. The general two possible approaches are considered. One is the jackknife method of resampling methods. The other is multiple imputation(MI). These two approaches are reviewed and compared through simulation studies.

• Journal of the Korean Data and Information Science Society
• /
• 제25권2호
• /
• pp.439-446
• /
• 2014

Quantile regression models with errors in variables have received a great deal of attention in the social and natural sciences. Some eorts have been devoted to develop eective estimation methods for such quantile regression models. In this paper we propose an orthogonal distance quantile regression model that eectively considers the errors on both input and response variables. The performance of the proposed method is evaluated through simulation studies.

• Journal of the Korean Statistical Society
• /
• 제36권4호
• /
• pp.523-542
• /
• 2007

In this paper we consider semiparametric random effect panel models that contain AR(p) disturbances. We derive the efficient score function and the information bound for estimating the slope parameters. We make minimal assumptions on the distribution of the random errors, effects, and the regressors, and provide semiparametric efficient estimates of the slope parameters. The present paper extends the previous work of Park et al.(2003) where AR(1) errors were considered.

• 한국지능시스템학회논문지
• /
• 제20권4호
• /
• pp.497-502
• /
• 2010

실내 복잡한 환경에서 이동 로봇의 정확한 이동 동작과 작업의 정확도를 높이기 위해서는 보다 정확한 위치 및 방향 추정이 요구된다. 본 논문에서는 실내 환경에서 이동 로봇이 실내 GPS(iGPS) 정보와 이동속도를 기반으로 위치 및 진행 방향을 강인하게 추정하는 기법을 제안하였다. 초음파를 사용한 iGPS를 기반으로 하는 실내 위치 추정 시스템은 외부 잡음과 초음파 자체의 오차를 가지고 있다. 외부 잡음과 자체 오차 한계를 가지는 환경에서 강인한 위치 및 방향 추정 시스템을 구현하기 위해 로봇의 이동 속도와 취득된 위치 정보의 불확실성을 고려한 소속 함수를 활용하여 강인한 추정 시스템을 제안하였다. 제안된 추정방법은 센서의 개수와 다양한 위치 오차를 고려한 모의실험을 통해 검증하였다.