• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.887-901
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• 2022

Estimation of the parameters for individual rainfall-rainfall events can lead to a different set of parameters for each event which result in lack of parameter identifiability. Moreover, it becomes even more ambiguous to determine a representative set of parameters for the watershed due to enhanced variability exceeding the range of model parameters. To reduce the variability of estimated parameters, this study proposed a parameter optimization framework with the simultaneous use of multiple rainfall-runoff events based on NSE as an objective function. It was found that the proposed optimization framework could effectively estimate the representative set of parameters pertained to their physical range over the entire watershed. It is found that the difference in NSE value of optimization when it performed individual and multiple rainfall events, is 0.08. Furthermore, In terms of estimating the observed floods, the representative parameters showed a more improved (or similar) performance compared to the results obtained from the single-event optimization process on an NSE basis.

• Structural Monitoring and Maintenance
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• v.6 no.4
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• pp.317-346
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• 2019

Performance assessment of pavements proves useful, in terms of handling the ride quality, controlling the travel time of vehicles and adequate maintenance of pavements. Roughness profiles provide a good measure of the deteriorating condition of the pavement. For the accurate estimates of pavement roughness from dynamic vehicle responses, vehicle parameters should be known accurately. Information on vehicle parameters is uncertain, due to the wear and tear over time. Hence, condition monitoring of pavement requires the identification of pavement roughness along with vehicle parameters. The present study proposes a scheme which estimates the roughness profile of the pavement with the use of accurate estimates of vehicle parameters computed in parallel. Pavement model used in this study is a two-layer Euler-Bernoulli beam resting on a nonlinear Pasternak foundation. The asphalt topping of the pavement in the top layer is modeled as viscoelastic, and the base course bottom layer is modeled as elastic. The viscoelastic response of the top layer is modeled with the help of the Burgers model. The vehicle model considered in this study is a half car model, fitted with accelerometers at specified points. The identification of the coupled system of vehicle-pavement interaction employs a coupled scheme of an unbiased minimum variance estimator and an optimization scheme. The partitioning of observed noisy quantities to be used in the two schemes is investigated in detail before the analysis. The unbiased minimum variance estimator (MVE) make use of a linear state-space formulation including roughness, to overcome the linearization difficulties as in conventional nonlinear filters. MVE gives estimates for the unknown input and fed into the optimization scheme to yield estimates of vehicle parameters. The issue of ill-posedness of the problem is dealt with by introducing a regularization equivalent term in the objective function, specifically where a large number of parameters are to be estimated. Effect of different objective functions is also studied. The outcome of this research is an overall measure of pavement condition.

• Environmental Engineering Research
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• v.15 no.3
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• pp.129-134
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• 2010

The optimization of experimental parameters, such as catalyst type, catalyst concentration, molar ratio of alcohol to oil and reaction temperature, on the transesterification for the production of rapeseed methyl ester has been studied. The Taguchi approach (Taguchi method) was adopted as the experimental design methodology, which was adequate for understanding the effects of the control parameters and to optimize the experimental conditions from a limited number of experiments. The optimal experimental conditions obtained from this study were potassium hydroxide as the catalyst, at a concentration of 1.5 wt %, and a reaction temperature of $60^{\circ}C$. According to Taguchi method, the catalyst concentration played the most important role in the yield of rapeseed methyl ester. Finally, the yield of rapeseed methyl ester was improved to 96.7% with the by optimal conditions of the control parameters which were obtained by Taguchi method.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.208-211
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• 1993

This paper presents the parameter design method for the desired time response of hydraulic track motor system of an industrial excavator. The dynamic response depends upon many component parameters such as motor displacement, spring constant and various valve coefficients. Most of them are to be determined to obtain the desired response while some parameters are fixed, or discrete for the off-the-shelf type components. The parameters might be selected through repeated simulations of the system once the system is mathematically represented. This paper, however, presents optimization technique to select two parameters using a parameter optimization technique. The variational approach is applied to the system equations which are represented as state equations and from those system equations derived are the adjoint equations. The gradients for each parameter also are formed for the iterations.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.225-228
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• 2002

When the fuzzy logic controller (FLC), which is designed based on the plant model, is applied to the real control system, satisfactory control performance may not be attained due to modeling errors from the plant model. In such cases, the control parameters of the controller must be adjusted to enhance control performance. Until now, the trial and error method has been used, consuming much time and effort. To resolve such problem, response surface methodology (RSM), a new method of adjusting the control parameters of the controller, is suggested. This method is more systematic than the previous trial and error method, and thus optimal solutions can be provided with less tuning. First, the initial values of the control parameters were determined through the plant model and the optimization algorithm. Then, designed experiments were performed in the region around the initial values, determining the optimal values of the control parameters which satisfy both the rise time and overshoot simultaneously.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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• pp.107-111
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• 2009

The parameters in the Horton's model which has well known as typical infiltration model were determined by the use of the optimization technique. It was assumed the initial infiltration capacity in this model was related to the antecedent precipitation per 10 days with linear combination. And both the parameters of the ultimate infiltration capacity and the decay factor were determined uniquely on a basin. Thus the optimal model's parameters representative to a basin were obtained and the Horton's infiltration equations by rainstorm events were determined. The data of ten rainstorm events for this study were observed at the Jeonjeokbigyo station located at the Selmacheon experimental basin that was $8.5\;km^2$ wide in the Imjin river.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.12
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• pp.14-20
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• 1998

Cutting fluid is a factor which has big effects on both machinability and environment in machining process. The loss of cutting fluids may be reduced by the optimization of machining parameters in process planning. In this study, the environmental impact of fluid loss is analyzed. The fluid loss models in milling process are constructed with the machining parameters. The models are utilized to obtain the optimal machining parameters to minimize the fluid loss. The factors with significant effects on the fluid loss are analyzed by ANOVA test. Finally, optimal parameters are suggested considering both machining economics and environmental impact. This study is expected to be used as a part of a framework for the environmental impact assessment of machining process.

• 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.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.7
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• pp.156-161
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• 1996

Accurate equivalent circuit modeling using multi-circuit optimization has been perfomred for detemining small-signal model of AlGaAs/GaAs HBTs. Three equivalent circuits for a cutoff biasing and two active biasing at different curretns are optimized simultaneously to fit gheir S parameters under the physics-based constrain that current-dependent elements for one of active circuits are connected to those for another circit multiplied by the ratio of two currents. The cutoff mode circuit and the physical constrain give the advantage of extracting physically acceptable parameters, because the number of unknown variables. After this optimization, three ses of optimized model S-parameters agree well with their measured S-parameters from 0.045 GHz to 26.5GHz.