• 응용통계연구
• /
• 제29권4호
• /
• pp.595-611
• /
• 2016

일반적으로 독성학 또는 약리학에서는 자료를 분석할 때 Hill Model과 같은 비선형 회귀모형을 사용한다. 비선형 회귀모형에서 모수의 추정량과 그것의 불확실성(uncertainty)에 대한 측도의 추정은 오차의 분산 구조에 영향을 받게 된다. 따라서 자료가 등분산인지 혹은 이분산인지에 따라 사용하여야 할 추정 방법이 달라져야 한다. 그러나 일반적으로 자료를 실제로 분석하기 전에는 오차의 분산구조에 대해서 잘 알 수 없다. 그러므로 오차의 분산구조에 로버스트한 추정 방법을 개발하는 것은 중요한 문제이다. 본 논문에서는 예비검정 방법을 기반으로 한 비선형 회귀모형에서의 모수 추정 방법을 제안하였다. 오차 분산의 등분산성에 대한 간단한 예비검정의 결과에 따라 보통 최소제곱 추정(ordinary Least Square Estimation) 방법과 반복 가중 최소제곱 추정(iterative weighted least square estimation) 방법을 사용하는 추정량을 정의하였다. 제안된 추정량은 모의실험 연구를 통하여 기존의 표준적인 추정량들과 그 성능을 비교하였다. 또한 미국의 National Toxicology Program으로부터 얻어진 실제자료를 사용하여 추정 방법들을 비교하였다.

• 한국항만학회지
• /
• 제15권1호
• /
• pp.87-97
• /
• 2001

The calculation of earthwork plays a major role in plan or design of many civil engineering projects, and thus it has become very important to advanced the accuracy of earthwork calculation. Current method used for estimating the volume of pit excavation assumes that the ground profile between the grid points is linear(trapezoidal rule), or nonlinear(simpson's formulas). In this paper the spot height method, least square method, and chamber formulas, Chen and Lin method are compared with the volumes of the pits in these examples. As a result of this study, algorithm of chen and Lin me쇙 by spline method should provide a better accuracy than the spot height method, least square method, chamber formulas. The Chen and Lin formulas can be used for estimating the excavation volume of a pit divide into a grid with unequal intervals. From the characteristics of the cubic spline polynomial, the modeling curve of the Chen and Lin method is smooth and matches the ground profile well. Generally speaking, the nonlinear profile formulas provide better accuracy than the linear profile formulas. The mathematical model mentioned make an offer maximum accuracy in estimating the volume of a pit excavation.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
• /
• pp.394-394
• /
• 2000

This Paper proposes a new nonlinear partial least square method that extends the linear PLS. Proposed nonlinear PLS uses self-organizing feature map as PLS outer relation and multilayer neural network as PLS inner regression method.

• 전기학회논문지
• /
• 제67권3호
• /
• pp.427-432
• /
• 2018

This paper uses a recursive least squares method to estimate the projectile motion trajectory of an object in real time. The equations of motion of the object are obtained considering the air resistance which occurs in the actual experiment environment. Because these equations consider air resistance, parameter estimation of nonlinear terms is required. However, nonlinear recursive least squares estimation is not suitable for estimating trajectory of projectile in that it requires a lot of computation time. Therefore, parameter estimation for real-time trajectory prediction is performed by recursive least square estimation after using Taylor series expansion to approximate nonlinear terms to polynomials. The proposed method is verified through experiments by using VICON Bonita motion capture system which can get three dimensional coordinates of projectile. The results indicate that proposed method is more accurate than linear Kalman filter method based on the equations of motion of projectile that does not consider air resistance.

• 전기학회논문지
• /
• 제56권7호
• /
• pp.1315-1320
• /
• 2007

In this paper, we introduce a new fuzzy model called fuzzy combined polynomial neural networks, which are based on the representative fuzzy model named polynomial fuzzy model. In the design procedure of the proposed fuzzy model, the coefficients on consequent parts are estimated by using not general least square estimation algorithm that is a sort of global learning algorithm but weighted least square estimation algorithm, a sort of local learning algorithm. We are able to adopt various type of structures as the consequent part of fuzzy model when using a local learning algorithm. Among various structures, we select Polynomial Neural Networks which have nonlinear characteristic and the final result of which is a complex mathematical polynomial. The approximation ability of the proposed model can be improved using Polynomial Neural Networks as the consequent part.

• Wind and Structures
• /
• 제17권4호
• /
• pp.451-464
• /
• 2013

This study develops an extended inverse input estimation algorithm with intelligent adaptive fuzzy weighting to effectively estimate the unknown input wind load of nonlinear structural systems. This algorithm combines the extended Kalman filter and recursive least squares estimator with intelligent adaptive fuzzy weighting. This study investigated the unknown input wind load applied on a tower structural system. Nonlinear characteristics will exist in various structural systems. The nonlinear characteristics are particularly more obvious when applying larger input wind load. Numerical simulation cases involving different input wind load types are studied in this paper. The simulation results verify the nonlinear characteristics of the structural system. This algorithm is effective in estimating unknown input wind loads.

• Archives of Pharmacal Research
• /
• 제28권5호
• /
• pp.598-603
• /
• 2005

The purpose of this study was to determine the influence of weight with gentamicin assay error on the Bayesian and nonlinear least squares regression analysis in 12 Korean appen dicitis patients. Gentamicin was administered intravenously over 0.5 h every 8 h. Three specimens were collected at 48 h after the first dose from all patients at the following times, just before regularly scheduled infusion, at 0.5 h and 2 h after the end of 0.5 h infusion. Serum gentamicin levels were analyzed by fluorescence polarization immunoassay technique with TDxFLx. The standard deviation (SD) of the assay over its working range had been determined at the serum gentamicin concentrations of 0, 2, 4, 8, 12, and 16 ${\mu}g$/mL in quadruplicate. The polynominal equation of gentamicin assay error was found to be SD (${\mu}g$/mL) = 0.0246-(0.0495C)+ (0.00203C$^2$). There were differences in the influence of weight with gentamicin assay error on pharmacokinetic parameters of gentamicin using the nonlinear least squares regression analysis but there were no differences on the Bayesian analysis. This polynominal equation can be used to improve the precision of fitting of pharmacokinetic models to optimize the process of model simulation both for population and for individualized pharmacokinetic models. The result would be improved dosage regimens and better, safer care of patients receiving gentamicin.

• 터널과지하공간
• /
• 제19권6호
• /
• pp.558-566
• /
• 2009

암석의 시간 의존적 거동은 기본적인 역학적 특성으로서 시간 의존적으로 거동을 분석하여 암반구조물의 파괴시간을 예측하는 것은 매우 중요하다. Voight가 제안한 재료 파괴 예측식($\ddot{\Omega}=A\dot{\Omega}^\alpha$, 여기서 $\Omega$는 변형률이나 변위와 같은 측정 가능한 물리량이고 A & $\alpha$는 상수이다)을 이용하여 터널, 사면 및 실내 크리프 시험으로부터 측정된 변위나 변형률로부터 파괴시간을 예측하고자 하였다. Voight식을 1차 및 2차 적분하여 구한 변위속도 및 변위식에 비선형최소자승법을 적용하여 A & $\alpha$를 구하였으며 이들 상수는 파괴시간을 예측하는데 사용되었다. 예측된 파괴시간은 실제 파괴시간과 잘 일치하는 것으로 나타났다. 크리프 변형률과 변형률속도에 선형역속도법을 적용하여 구한 예측 파괴시간은 변형률과 변형률속도를 이용하여 구한 파괴시간보다 오차가 큰 것으로 나타났다.

• 한국정보디스플레이학회:학술대회논문집
• /
• 한국정보디스플레이학회 2003년도 International Meeting on Information Display
• /
• pp.32-35
• /
• 2003

Nonlinear parameterization of OLED device from measurements of bias dependence of impedance spectra and parameter extraction using Levenberg-Marquardt complex nonlinear least square regression algorithm based on resistor-capacitor equivalent circuit model enables computer simulation of OLED power driving characteristics in forms of square-wave or sinusoidal output signal at arbitrary conditions. We introduce developed OLED power driving simulation software and discuss transient responses in voltage-or current-controlled operations as well as nonlinear characteristics of OLED, by presenting both the simulation and experimental results. This OLED simulation technique using impedance spectroscopy is extremely useful in predicting performance of the nonlinear device, especially in time-domain analysis of device operation.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.419-424
• /
• 1992

A robust nonlinear predictive control strategy using a disturbance estimator is presented. The disturbance estimator is comprised of two parts: one is the disturbance model parameter adaptation and the other is future disturbance prediction. RLSM(recurrsive least square method) with a forgetting factor is used to de the uncertain distance model parameters and for the future disturbance prediction, future process outputs and inputs projected by the process model are used. The simulation results for chemical reactors indicate that a substantial improvement in nonlinear predictive control performance is possible using the disturbance estimator.