• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.749-754
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• 2015

This article presents Bayesian approach to regression splines with knots on a grid of equally spaced sample quantiles of the independent variables under functional measurement error model.We consider small area model by using penalized splines of non-linear pattern. Specifically, in a basis functions of the regression spline, we use radial basis functions. To fit the model and estimate parameters we suggest a hierarchical Bayesian framework using Markov Chain Monte Carlo methodology. Furthermore, we illustrate the method in an application data. We check the convergence by a potential scale reduction factor and we use the posterior predictive p-value and the mean logarithmic conditional predictive ordinate to compar models.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.97.2-97
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• 2001

This work is concerned with the improvement of the productivity and the product quality in the polymerization reactors by using model-on-demand predictive control(MoDPC). This technique is applied to a continuous styrene polymerization reactor and a semibatch methyl methacrylate (MMA)/vinyl acetate(VAc) copolymerization reactor. The regress is constructed with the most influential variables the conversion and the jacket inlet temperature for the styrene polymerization reactor, and the free volume and the reactor temperature for the MMA/VAc copolymerization reactor through open loop operations. From the simulation results for setpoint tracking and disturbance rejection problems, it is demonstrated that the MoDPC shows ...

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.37 no.1 s.109
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• pp.67-72
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• 2005

In the grade change operations inputs and outputs are highly correlated and application of conventional linear feedback control methods such as PID schemes might lead to poor control performance. In this study the neural networks model for the grade change operation is trained by using bilinear terms which can represent non-linear characteristics of grade change operations. The inverse model of the grade change operation is obtained from training and the optimal input variables are computed from the trained neural networks as well. The proposed bilinear inverse model predictive control scheme was found out to showlittle discrepancy between simulated outputs and setpoints.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.468-473
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• 1998

A mathematical model was developed for a continuous re-actor in which free radical polymerization of methyl methacrylate (MMA) occurred. Elementary reactions considered in this study were initiation, propagation, termination, and chain transfers to monomer and solvent. The reactor model took into account the density change of the reactor contents and the gel effect. A control system was designed for a continuous reactor using extended Kalman filter (EKF) based non-linear model predictive controller (NLMPC) to control the conversion and the weight average molecular weight of the polymer product. Control input variables were the jacket inlet temperature and the feed flow rate. For the purpose of validation of the control strategy, on-line digital control experiments were conducted with densitometer and viscometer for the measurement of the polymer properties. Despite the com-plex and nonlinear features of the polymerization reaction system, the EKF based NLMPC performed quite satisfactorily for the property control of the continuous polymerization reactor.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.6
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• pp.582-587
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• 1997

This paper deals with the control problem under nonlinear boiler systems with noise, and input constraints. MCMBPC(Multivariable Constrained Model-Based Predictive Controller) proposed by Wilkinson et al.[10,11] is used and nominal model is modified in this paper in order to applied to nonlinear boiler systems with feed-forward terms. The solution of the cost function optimization constrained on input and/or output variables is achieved using quadratic programming, via singular value decomposition(SVD). The controller designed is shown to satisfy the constraints and to have excellent tracking performance via simulation applied to nonlinear dynamic drum boiler turbine model for 16OMW unit.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.49 no.4
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• pp.246-255
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• 2000

This paper deals with a novel full digital control method of the three-phase PWM inverter for UPS. The voltage and current of output filter capacitor as state variables are the feedback control input. In addition, a double deadbeat control consisting of a d-q current minor loop and a d-q voltage major loop, both with precise decoupling, have been developed. The switching pulse width modulation based on SVM is adopted so that the capacitor current should be exactly equal to its reference current. In order to compensate the calculation time delay, the predictive control is achieved by the current·voltage observer. The load prediction is used to compensate the load disturbance by disturbance observer with deadbeat response. The experimental results show that the proposed system offers an output voltage with THD less than 2% at a full nonlinear load.

• The Journal of Information Technology
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• v.2 no.1
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• pp.191-207
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• 1999

The study is in attempting for reviewing the selection problem of the measurement and the model, concerning a consumer satisfaction model. Therefore, a common model, which measures degree of consumer satisfaction by an arithmetic mean from measurement method including data, which assess compulsively the attribution and the importance to consumers, shows the problems of a field application. There showed a high predictive validity in the model of a singular item using the degree of a general satisfaction rather than a detailed assessment. However, the single model needs the model of consumer satisfaction from the using of plural items, because of the field problems that produce in an alternative application. There showed a high significance level in the model including variables, which are showing a high correlation between purchase intention and predictive validity.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.20 no.1
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• pp.6-17
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• 2013

Purpose: The purpose of this study was propose and test a predictive model that could explain and predict factors influencing the sexual satisfaction of women with diabetes mellitus. Method: The conceptual frame for this study was formed as a hypothesized model based on Roy's adaptation model. Participants for this study were 240 out-patient women from P university hospital in Y city. The data were analyzed using SPSS 18.0 and AMOS 19.0 program. Results: The paths that had direct effects on sexual satisfaction, and were statistically significant were showing intimacy with spouse, and sexual function. The explanatory power of these variables for sexual satisfaction was 64%. Conclusion: The results of the study suggest that it is necessary for enhancement of sexual satisfaction for women with diabetes to increase intimacy with husband, and that sexual function, frequency of exercise, adequate glycemic control be maintained, and depression decreased.

• Journal of Navigation and Port Research
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• v.47 no.2
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• pp.66-74
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• 2023

With the increase of interest in developing Maritime Autonomous Surface Ships (MASS), an optimal ship route planning is gradually gaining popularity as one of the important subsystems for autonomy of modern marine vessels. In the present paper, an optimal ship route planning model for MASS is proposed using a nonlinear MPC approach together with a nonlinear MMG model. Results drawn from this study demonstrated that the optimization problem for the ship route was successfully solved with satisfaction of the nonlinear dynamics of the ship and all constraints for the state and manipulated variables using the nonlinear MPC approach. Given that a route generation system capable of accounting for nonlinear dynamics of the ship and equality/inequality constraints is essential for achieving fully autonomous navigation at sea, it is expected that this paper will contribute to the field of autonomous vehicles by demonstrating the performance of the proposed optimal ship route planning model.

• Industrial Engineering and Management Systems
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• v.12 no.4
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• pp.406-415
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• 2013

The present study examines a set of financial ratios in predicting the up or down movements of stock prices in the context of a securities law, the Sarbanes-Oxley Act of 2002 (SOA), controlling for macroeconomic variables. Using the logistic regression with proxy betas to alleviate the incompatibility problem between the firm-specific financial ratios and macroeconomic indicators, we report evidence that financial ratios are meaningful predictors of stock price changes, which subdue the influence of macroeconomic indicators on stock returns, and more importantly that the SOA truly improves the stock price predictability of financial ratios for the markup sample. The empirical results further suggest that industry and time effects exist and that for the markdown sample the SOA actually deteriorates the predictive power of financial ratios.