• Title/Summary/Keyword: parameter estimate

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Kernel Machine for Poisson Regression

  • Hwang, Chang-Ha
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.3
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    • pp.767-772
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    • 2007
  • A kernel machine is proposed as an estimating procedure for the linear and nonlinear Poisson regression, which is based on the penalized negative log-likelihood. The proposed kernel machine provides the estimate of the mean function of the response variable, where the canonical parameter is related to the input vector in a nonlinear form. The generalized cross validation(GCV) function of MSE-type is introduced to determine hyperparameters which affect the performance of the machine. Experimental results are then presented which indicate the performance of the proposed machine.

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A Combination Capture-Recapture and Line Transect Model in Clustered Population

  • Choi, Jin-Sik;Pyong, Nam-Kung
    • Communications for Statistical Applications and Methods
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    • v.6 no.3
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    • pp.729-748
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    • 1999
  • In this paper we present combined estimator of capture-recapture and line transect model using bivariate detection function and detection probability according to objects being in cluster population. Here bivariate detection function use distance and cluster size. The simulation shows that combined estimator approaches the more true value the larger size parameter. Therefore this estimator using the bivariate detection function is more efficient in estimate the population size and density by size parameter.

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선형 저수지 유형의 parameter 연구

  • 서영재;고재웅
    • Proceedings of the Korea Water Resources Association Conference
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    • 1987.07a
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    • pp.151-158
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    • 1987
  • The purpose of thes study is to estimate the parameters of linear reservoir models in order to derive the instantaneous unit hydrograph from a given small experimental watershed. The linear reservoir model is a conceptual model, consisting of cascade or parallel equal linear reservoirs, preceded by a linear channel which involved NASH, SLR(single linear reservoir)and 2-PLR(two-parallel linear reservoir)model. The NASH model have two parameters N and K, single linear reservoir has one parameter K1 and two-parallel linear reservoirs have two parameters K1, K2;where N denote the number of reservoirs and K is the storage coefficient of each reservoirs.

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RISK EVALUATION OF CARBON MONOXIDE IN COMPARTMENT FIRE

  • Kim, Kwang Il
    • Proceedings of the Korea Institute of Fire Science and Engineering Conference
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    • 1997.11a
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    • pp.66-76
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    • 1997
  • In order to investigate the generation of carbon monoxide and heat loss of incomplete combustion in compartment fires, an experiment was conducted in a small scale compartment by using methanol as a fuel. The concentration of carbon monoxide and the toxicity parameter showed high values when the mass air - to - fuel stoichiometric ratio is under 1.0. The constitution of the combustion gas was showed to estimate it from the . The heat loss due to incompleteness of combustion is about one third of heat of combustion in case of under 1.0.

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Optimization of LQR method for the active control of seismically excited structures

  • Moghaddasie, Behrang;Jalaeefar, Ali
    • Smart Structures and Systems
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    • v.23 no.3
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    • pp.243-261
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    • 2019
  • This paper introduces an appropriate technique to estimate the weighting matrices used in the linear quadratic regulator (LQR) method for active structural control. For this purpose, a parameter is defined to regulate the relationship between the structural energy and control force. The optimum value of the regulating parameter, is determined for single degree of freedom (SDOF) systems under seismic excitations. In addition, the suggested technique is generalized for multiple degrees of freedom (MDOF) active control systems. Numerical examples demonstrate the robustness of the proposed method for controlled buildings under a wide range of seismic excitations.

Parameter Estimation of Permanent Magnet Synchronous Motors using a Least Squares Method (최소자승법을 이용한 영구자석 동기전동기의 파라미터 추정)

  • Kwon, Ki-Hoon;Lee, Kyo-Beum
    • Proceedings of the KIPE Conference
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    • 2018.11a
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    • pp.175-176
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    • 2018
  • This paper presents a method to estimate the parameter of permanent magnet synchronous motor using a least squares method. The approximate solution of the linear simultaneous equations is obtained by the pseudoinverse least squares method of the input current and output voltage data of the current controller. It is possible to obtain the current response of the same bandwidth to the general control target by using the Pole-zero Cancellation technique. This paper verifies the performance of the proposed method by comparing the results of estimation of parameters of different motors by simulation.

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Inductance Estimation of Permanent Magnet Type Transverse Flux Rotating Motor Using Dynamic-Simulation (Dynamic-Simulation을 통한 영구자석형 횡자속 회전기의 인덕턴스 추정)

  • Kim, Kwang-Woon;Kim, Ji-Won;Jung, Yeon-Ho;Lee, Ji-Young;Kang, Do-Hyun;Chang, Jung-Hwan
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.4
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    • pp.722-727
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    • 2010
  • This paper presents Dynamic-Simulation to estimate the inductance of a permanent magnet type transverse flux rotating motor by applying the real-time parameter estimation theory. As transverse flux rotating motor has the complex structure, it can be happen to some errors between real value and designed one with respect to the inductance. To reduce this kinds of errors, the real-time parameter estimation theory was applied to dynamic-simulation. And then, By comparing the estimated inductance and designed one, it is realized that the real-time parameter estimation theory can be applied in the permanent magnet type transverse flux rotating motor.

A Parameter Estimation Method of Multiple Time Interval for Low Frequency Oscillation Analysis (저주파진동 해석을 위한 다구간 파라미터 추정 방법)

  • Shim, Kwan-Shik;Kim, Sang-Tae;Choi, Joon-Ho;Nam, Hae-Kon;Ahn, Seon-Ju
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.63 no.7
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    • pp.875-882
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    • 2014
  • In this paper, we propose a new parameter estimation method that can deal with the data of multiple time intervals simultaneously. If there are common modes in the multiple time intervals, it is possible to create a new polynomial by summing the coefficients of the prediction error polynomials of each time interval. By calculating the roots of the new polynomial, it is possible to estimate the common modes that exist in each time interval. The accuracy of the proposed parameter estimation method has been proven by using appropriate test signals.

High Performance of Self Scheduled Linear Parameter Varying Control with Flux Observer of Induction Motor

  • Khamari, Dalila;Makouf, Abdesslam;Drid, Said;Chrifi-Alaoui, Larbi
    • Journal of Electrical Engineering and Technology
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    • v.8 no.5
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    • pp.1202-1211
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    • 2013
  • This paper deals with a robust controller for an induction motor (IM) which is represented as a linear parameter varying systems. To do so linear matrix inequality (LMI) based approach and robust Lyapunov feedback are associated. This approach is related to the fact that the synthesis of a linear parameter varying (LPV) feedback controller for the inner loop take into account rotor resistance and mechanical speed as varying parameter. An LPV flux observer is also synthesized to estimate rotor flux providing reference to cited above regulator. The induction motor is described as a polytopic LPV system because of speed and rotor resistance affine dependence. Their values can be estimated on line during systems operations. The simulation and experimental results largely confirm the effectiveness of the proposed control.

An Application of the Instrumental Variable Method(IVM) to a Parameter Identification of a Noise Contaminated Bearing Test Rig (IV 방법을 이용한 잡음이 포함된 베어링 실험 장치의 동특성 파라미터 추출)

  • 이용복;김창호;최동훈
    • Journal of KSNVE
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    • v.6 no.5
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    • pp.679-684
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    • 1996
  • The Instrumental Variable Method(IVM), modified from least square algorithm, is applied to parameter identification of a noise contaminated bearing test rig. The signal to noise ratio included in Frequency Response Function(FRF) can cause significant errors in parameter identification. Therefore, among several candidates of parameter identification method, results of the applied IVM were compared with noise-contaminated least square method. This study shows that the noise-contaminated least square method can have indonsistent accuracy depending on the degree of noise level, while the IVM has robuster performance to signal to noise ratio than least square method.

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