• Proceedings of the KIEE Conference
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• 2005.07d
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• pp.2513-2515
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for leaming in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of Butter-Worth analog filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate Butter-Worth analog filter parameter using the genetic algorithm.

• International Area Studies Review
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• v.14 no.3
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• pp.35-60
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• 2010

In this paper, we develop a dynamic structural model based on a dynamic supergame and measure market power for the Dallas-Forth Worth fluid milk market in the U.S. In particular, we compare the conduct parameter estimates from a static model with that from the dynamic model and illustrate bias in the market-power measure in a static model. And we also analyze the cyclical behavior of firm conduct. We find that the conduct parameter in a static model underestimates true market power if firms' behaviors are posited by a dynamic oligopoly game. We also verify that firm conduct in the Dallas-Forth Worth fluid milk market is countercyclical against demand shocks and expected future cost shocks. Our results indicate that the firms' conduct in the Dallas-Forth Worth fluid milk market is consistent with what dynamic oligopoly models predict. This implies that the firms consider not only the contemporary reactions of the other firms' but also future market competition. Therefore, the measurement of market power requires the specification of fully dynamic pricing relationship.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1398-1406
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• 2024

The control rod worth is a key safety parameter required to be measured in commercial pressurized water reactors (PWRs). Conventionally, the control rod worth is measured after reaching the critical state, which occupies the considerable time in the zero-power physics test. In this study, an efficient control-rod worth measurement technique has been proposed based on the improved neutron-source multiplication method, which can be implemented with the source-range detector count rates in the subcritical states. Moreover, the noise reduction technique has been adopted to smooth the large fluctuation existing in the original signals. In order to verify the engineering performance of the proposed measurement technique, the measured source-range detector count rates during the rod withdrawal process before reaching critical state in a CNP1000 reactor have been employed. It demonstrated that almost all estimated results of control rod worth satisfy the engineering acceptance criteria, except one control rod with the relative difference over 10 %, which indicates the capability of the proposed method in estimating control rod worth.

• Nuclear Engineering and Technology
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• v.51 no.4
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• pp.963-967
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• 2019

Accurate measurement of the reactivity worth of safety rods is very important for the safe reactor operation, in normal and emergency conditions. In this paper, the reactivity worth of safety rods in Heavy Water Zero Power Reactor (HWZPR) in the new lattice pitch is measured by advanced source jerk method. The average of the results related to two different detectors is equal to 29.88 mk. In order to verify the result, this parameter was compared to the previously measured value by subcritical to critical approach. Different experiment results are finally compared with corresponding calculated result. Difference between the average experimental and calculated results is equal to 2.2%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.1-8
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• 2021

As a nation experiencing rapid economic growth, South Korea and its government have made a continuous effort toward efficient research investments to achieve transformation of the Korean industry for the fourth industrial revolution. To achieve the maximum effectiveness of the research investments, it is necessary to evaluate its funding's worth and default risk. Thus, incorporating the concepts of the Black-Scholes-Merton model and the Greeks, this study develops a default-risk evaluation model in the foundation of a system dynamics methodology. By utilizing the proposed model, this study estimates the monetary worth and the default risks of research funding in the public and private sectors of Information and Communication technologies, along with the sensitivity of the R&D economic worth of research funding to changes in a given parameter. This study finds that the public sector has more potential than the private sector in terms of monetary worth and that the default risks of three types of research funding are relatively high. Through a sensitivity analysis, the results indicate that uncertainty in volatility, operation period, and a risk-free interest rate has trivial impacts on the monetary worth of research funding, while volatility has large impacts on the default risk among the uncertain factors.

• Proceedings of the KIEE Conference
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• 2005.05a
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• pp.15-17
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of nonlinear IIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate nonlinear IIR filter parameter using the genetic algorithm.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.502-504
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• 2005

Recently genetic algorithm techniques have widely used in adaptive and control schemes for production systems. However, generally it costs a lot of time for learning in the case applied in control system. Furthermore, the physical meaning of genetic algorithm constructed as a result is not obvious. And this method has been used as a learning algorithm to estimate the parameter of a genetic algorithm used for identification of the process dynamics of FIR filter and it was shown that this method offered superior capability over the genetic algorithm. A genetic algorithm is used to solve the parameter identification problem for linear and nonlinear digital filters. This paper goal estimate FIR filter parameter using the genetic algorithm.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1775-1782
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• 2023

Several reactor physics commissioning experiments were conducted to obtain the neutronic parameters at the beginning of the G.A. Siwabessy Multi-purpose Reactor (RSG-GAS) operation. These parameters are essential for the reactor to safety operate. Leveraging the experimental data, this study evaluated the calculated core reactivity, control rod reactivity worth, integral control rod reactivity curve, and fuel reactivity. Calculations were carried out with Serpent 2 code using the latest neutron cross-section data ENDF/B-VIII.0. The criticality calculations were carried out for the RSG-GAS first core up to the third core configuration, which has been done experimentally during these commissioning periods. The excess reactivity for the second and third cores showed a difference of 510.97 pcm and 253.23 pcm to the experiment data. The calculated integral reactivity of the control rod has an error of less than 1.0% compared to the experimental data. The calculated fuel reactivity value is consistent with the measured data, with a maximum error of 2.12%. Therefore, it can be concluded that the RSG-GAS reactor core model is in good agreement to reproduce excess reactivity, control rod worth, and fuel element reactivity.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1137-1146
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• 2010

There are a lot of methods to predict the result of a game and many forecasting researches have been studied. Among many methods, if a statistical model including some realistic random variables is used to forecast, more accurate prediction could be expected than any others. In this work, Bradley-Terry model is considered to predict results of 2010 South Africa World Cup games via paired comparison method. This prediction model includes some random variables which affect the results of games. The worth parameters for each country in this model are convergence values obtained by using Newton-Raphson algorithm. With this model, we can forecast top 16 among 32 countries and up to who will win the victory. Final results of 2010 South Africa World Cup games are compared with this prediction and discuss further works.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.10
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• pp.42-47
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• 2019

Helical machining is an efficient method for machining holes using an endmill. In this study, a surface roughness prediction model was constructed for improving the productivity of hole machining. Experiments were conducted to form holes by the helical machining of AL6061-T4 aluminum sheets and correlation analysis was performed to examine the relationships between the variables based on the measured results. Meanwhile, a regression analysis technique was used to construct and evaluate the prediction model. Through these analyses, the parameter which has the greatest influence on the surface roughness when the hole is formed by the helical machining is the feed, followed by the number of revolutions of the endmill. Moreover, for the axial feed of the endmill, it was concluded that the influence of the surface roughness is small compared to the other two parameters but it is a factor worth considering to improve the accuracy when constructing the predictive model.