• Title/Summary/Keyword: parameters estimation

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Estimating Parameters of Field Lifetime Data Distribution Using the Failure Reporting Probability (고장 보고율을 이용한 현장 수명자료 분포의 모수추정)

  • Kim, Young Bok;Lie, Chang Hoon
    • Journal of Korean Institute of Industrial Engineers
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    • v.33 no.1
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    • pp.52-60
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    • 2007
  • Estimating parameters of the lifetime distribution is investigated when field failure data are not completelyreported. To take into account the reality and the accuracy of the estimates in such a case, the failure reportingprobability is incorporated in estimating parameters, Firstly, method of maximum likelihood estimate (MLE) isused to estimate parameters of the lifetime distribution when failure reporting probability is known, Secondly,Expectation and Maximization (EM) algorithm is used to estimate the failure reporting probability and parame-ters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both cases,procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simula-tion results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

Development of an Event Rainfall-Runoff Model in Small Watersheds

  • Lee, Sang-Ho;Lee, Kil-Seong
    • Korean Journal of Hydrosciences
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    • v.6
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    • pp.81-98
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    • 1995
  • A linear reservoir rainfall-runoff system was developed as a rainfall-runoff event simulation model. It was achieved from large modification of runoff function method. There are six parameters in the model. Hydrologic losses consist of some quantity of initial loss and some ratio of rainfall intensity followed by initial loss. The model has analytical routing equations. Hooke and Jaeves algorithm was used for model calibration. Parameters were estimated for flood events from '84 to '89 at Seomyeon and Munmak stream gauges, and the trends of major parameters were analyzed. Using the trends, verifications were performed for the flood event in September 1990. Because antecedent rainfalls affect initial loss, future researches are required on such effects. The estimation method of major parameters should also be studied for real-time forecasting.

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Symbolic-numeric Estimation of Parameters in Biochemical Models by Quantifier Elimination

  • Orii, Shigeo;Anai, Hirokazu;Horimoto, Katsuhisa
    • Proceedings of the Korean Society for Bioinformatics Conference
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    • 2005.09a
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    • pp.272-277
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    • 2005
  • We introduce a new approach to optimize the parameters in biological kinetic models by quantifier elimination (QE), in combination with numerical simulation methods. The optimization method was applied to a model for the inhibition kinetics of HIV proteinase with ten parameters and nine variables, and attained the goodness of fit to 300 points of observed data with the same magnitude as that obtained by the previous optimization methods, remarkably by using only one or two points of data. Furthermore, the utilization of QE demonstrated the feasibility of the present method for elucidating the behavior of the parameters in the analyzed model. The present symbolic-numeric method is therefore a powerful approach to reveal the fundamental mechanisms of kinetic models, in addition to being a computational engine.

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Ultrasonographic Estimation of Prostatic Size of Toy Breed Dogs (소형견의 전립선 크기에 관한 초음파적 연구)

  • 윤화중;최치봉;배춘식
    • Journal of Veterinary Clinics
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    • v.17 no.1
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    • pp.168-172
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    • 2000
  • Prostatic length and height on sagittal images and prostatic width and height on transverse images were measured ultrasonographically to establish upper limit of the prostate in 45 dogs which were clinically healthy and sexuallly intact. Linear 5regression and correlatin analysis were performed between prostatic parameters(length and height on sagittal images & width and height on transverse images) and parameters related to body size(body weight, left kidney length) and age of the dogs. Prostatic parameters were significantly correlated with body size and age of the dogs. Maximum predicted values with body weight and age for prostatic parameters were determined based o the upper limit of the 95% confidence interval of the mean predicted values. Such values should be useful for the small animal clinicians in determining if the prostate gland is too large for a given body weight and age, and may contribute to clinicl signs.

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고장 보고율을 이용한 현장 수명자료 분포의 모수추정

  • Park, Tae-Ung;Kim, Yeong-Bok;Lee, Chang-Hun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.678-685
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    • 2005
  • Estimating parameters of the lifetime distribution is investigated when field failure data are not completely reported. To take into account the reality and the accuracy of the estimates in such a case, the failure reporting probability is incorporated in estimating parameters. Firstly, method of maximum likelihood estimate(MLE) is used to estimate parameters of the lifetime distribution when failure reporting probability is known. Secondly, Expectation and Maximization(EM) algorithm is used to estimate the failure reporting probability and parameters of the lifetime distribution simultaneously when failure reporting probability is unknown. For both case, procedures of estimation are illustrated for single Weibull distribution and mixed Weibull distribution. Simulation results show that MLE obtained by the proposed method is more accurate than the conventional MLE.

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Control Performance Improvement for Linear Compressors (리니어 컴프레서의 제어성능 향상)

  • Kim, Gyu-Sik
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.56 no.3
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    • pp.594-599
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    • 2007
  • A dosed-loop sensorless stroke control system for a linear compressor has been designed. The motor parameters are identified as a function of the piston position and the motor current. They are stored in ROM table and used later for the accurate estimation of piston position. Also it was attempted to approximate the identified motor parameters to the 2nd-order surface functions. The 2nd-order surface functions are divided into 2 or 4 sub-sections for more precise identification of motor parameters. Some experimental results are given in order to show the feasibility of the proposed control schemes for linear compressors.

Joint parameter identification of a cantilever beam using sub-structure synthesis and multi-linear regression

  • Ingole, Sanjay B.;Chatterjee, Animesh
    • Structural Engineering and Mechanics
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    • v.45 no.4
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    • pp.423-437
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    • 2013
  • Complex structures are usually assembled from several substructures with joints connecting them together. These joints have significant effects on the dynamic behavior of the assembled structure and must be accurately modeled. In structural analysis, these joints are often simplified by assuming ideal boundary conditions. However, the dynamic behavior predicted on the basis of the simplified model may have significant errors. This has prompted the researchers to include the effect of joint stiffness in the structural model and to estimate the stiffness parameters using inverse dynamics. In the present work, structural joints have been modeled as a pair of translational and rotational springs and frequency equation of the overall system has been developed using sub-structure synthesis. It is shown that using first few natural frequencies of the system, one can obtain a set of over-determined system of equations involving the unknown stiffness parameters. Method of multi-linear regression is then applied to obtain the best estimate of the unknown stiffness parameters. The estimation procedure has been developed for a two parameter joint stiffness matrix.

VALIDITY OF NDVI-BASED BIOPHYSICAL PARAMETERS FOR ECOSYSTEM MODELS

  • Lee, Kyu-Sung;Jang, Ki-Chang;Kim, Tae-Geun;Lee, Seung-Ho;Cho, Hyun-Guk
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.543-546
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    • 2006
  • NDVI has been very frequently used to estimate several biophysical parameters that are required for ecosystem models. Leaf area index (LAI), canopy closure, and biomass are among those biophysical parameters that are estimated by empirical relationship with NDVI. However, the type of remote sensing signals (raw DN value, at-sensor radiance, atmospherically corrected reflectance) used can vary the calculation of NDVI. In this study, we tried to attempt to compare the influence of NDVI linked with forest LAI for the watershed-scale ecosystem models to estimate evapotranspiration. Landsat ETM+ data were used to obtain various NDVI values over the study area in central Korea. The NDVI-based LAI and the resultant evapotranspiration estimation were greatly varied by the remote sensing signal applied.

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The Estimation of Theoretical Semivariogram Adapting Genetic Algorithm for Kriging

  • Ryu, Je-Seon;Park, Young-Sun;Cha, Kyung-Joon
    • Communications for Statistical Applications and Methods
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    • v.11 no.2
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    • pp.355-368
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    • 2004
  • In order to use Kriging, one has to estimate three parameters(nugget, sill and range) of semivariogram, which shows the relationship in the given two sites. A visual fit of the semivariogram parameters to a few standard models is widely used. But, it does not give the suitable results and not provide the automated process of Kriging. The gradient based nonlinear least squares is another choices to estimate three parameters, but it has some problems such as initial value problem. In this paper, we suggest the genetic algorithm as a compatible alternative method to solve the above mentioned problem. Finally, we estimate three parameters of semivariogram of rain-fall by adapting the genetic algorithm, compute Kriging estimate and conclude its effectiveness and compatibility.

Estimation of Qualities and Inference of Operating Conditions for Optimization of Wafer Fabrication Using Artificial Intelligent Methods

  • Bae, Hyeon;Kim, Sung-Shin;Woo, Kwang-Bang
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.1101-1106
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    • 2005
  • The purpose of this study was to develop a process management system to manage ingot fabrication and the quality of the ingot. The ingot is the first manufactured material of wafers. Operating data (trace parameters) were collected on-line but quality data (measurement parameters) were measured by sampling inspection. The quality parameters were applied to evaluate the quality. Thus, preprocessing was necessary to extract useful information from the quality data. First, statistical methods were employed for data generation, and then modeling was accomplished, using the generated data, to improve the performance of the models. The function of the models is to predict the quality corresponding to the control parameters. The dynamic polynomial neural network (DPNN) was used for data modeling that used the ingot fabrication data.

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