• Nuclear Engineering and Technology
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• v.27 no.3
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• pp.336-343
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• 1995

The Self Tuning Regulator(STR) method which is an approach of adaptive control theory, is ap-plied to design the fully automatic power controller of the nonlinear reactor model. The adaptive control represent a proper approach to design the suboptimal controller for nonlinear, time-varying stochastic systems. The control system is based on a third­order linear model with unknown, time-varying parameters. The updating of the parameter estimates is achieved by the recursive extended least square method with a variable forgetting factor. Based on the estimated parameters, the output (average coolant temperature) is predicted one-step ahead. And then, a weighted one-step ahead controller is designed so that the difference between the output and the desired output is minimized and the variation of the control rod position is small. Also, an integral action is added in order to remove the steady­state error. A nonlinear M plant model was used to simulate the proposed controller of reactor power which covers a wide operating range. From the simulation result, the performances of this controller for ramp input (increase or decrease) are proved to be successful. However, for step input this controller leaves something to be desired.

• Journal of Korea Water Resources Association
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• v.45 no.2
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• pp.229-242
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• 2012

This study presents a physical habitat modeling of adult Zacco platypus in a reach of the Dalcheon Stream located downstream of the Goesaan Dam. CASiMiR model is used to estimate habitat suitability index based on the fuzzy logic. Results are compared with those from River2D model, which uses habitat preference curve for habitat suitability index. Hydraulic data simulated by River2D are used as input data for CASiMiR model after verification against field measurements. The result shows that the habitat suitability of the adult Zacco platypus is maximum around the riffle area located upstream of the bend. CASiMiR and River2D estimate the maximum weighted usable areas at the discharge rates of 7.23 $m^3/s$ and 9.0 $m^3/s$, respectively. Overall comparison of the two models employed in this study indicates that CASiMiR model overestimates the weighted usable area by 0.3~25.3% compared with River2D model in condition of drought flow (Q355), low flow (Q275), normal flow (Q185), and average-wet flow (Q95).

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.2
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• pp.597-604
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• 2014

In this study, we investigate to show the limitations of current bus arrival time estimation model based on each bus route, and to propose a bus arrival time estimation model based on a bus stop to overcome these limitations. Using the characteristic of bus arrival time calculated on travel time between two bus stops, we develop a model to estimate bus arrival times with the data of all buses traveling the same section regardless of bus route numbers. In the proposed model, an estimated arrival time is calculated by weighted moving average method, and verification between observed value and estimated time is performed on the basis of RMSE. Error was reduced by up to 20% compared to the existing models and the data update period was reduced by more than half that is related to the accuracy of bus arrival time information. We expect to solve the following problems with the suggested method: sudden increase or decrease in arrival time of the bus, the difference of the expected arrival times at the same stop between two or more buses having different route numbers, and impossibility of offering information of a bus if the bus is not operated with the designated schedule.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.147-153
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• 2017

The mortality rate in industrial accidents in South Korea was 11 per 100,000 workers in 2015. It's five times higher than the OECD average. Economic losses due to industrial accidents continue to grow, reaching 19 trillion won much more than natural disaster losses equivalent to 1.1 trillion won. It requires fundamental changes according to industrial safety management. In this study, We classified the risk of accidents in industrial complex of Ulju-gun using spatial analytics and data mining. We collected 119 data on accident data, factory characteristics data, company information such as sales amount, capital stock, building information, weather information, official land price, etc. Through the pre-processing and data convergence process, the analysis dataset was constructed. Then we conducted geographically weighted regression with spatial factors affecting fire incidents and calculated the risk of fire accidents with analytical model for combining Boosting and CART (Classification and Regression Tree). We drew the main factors that affect the fire accident. The drawn main factors are deterioration of buildings, capital stock, employee number, officially assessed land price and height of building. Finally the predicted accident rates were divided into four class (risk category-alert, hazard, caution, and attention) with Jenks Natural Breaks Classification. It is divided by seeking to minimize each class's average deviation from the class mean, while maximizing each class's deviation from the means of the other groups. As the analysis results were also visualized on maps, the danger zone can be intuitively checked. It is judged to be available in different policy decisions for different types, such as those used by different types of risk ratings.

• The Journal of Bigdata
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• v.7 no.1
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• pp.75-87
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• 2022

This study investigates a dynamic flexible flow shop scheduling problem under uncertain rework operations for an automobile pipe production line. We propose a weighted dispatching rule (WDR) based on the multiple dispatching rules to minimize the weighted sum of average flowtime and tardiness. The set of weights in WDR should be carefully determined because it significantly affects the performance measures. We build a discrete-event simulation model and propose a genetic algorithm to optimize the set of weights considering complex and variant operations. The simulation experiments demonstrate that WDR outperforms the baseline dispatching rules in average flowtime and tardiness.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.825-835
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• 2008

Multivariate GARCH(MGARCH) has been useful in financial studies and econometrics for modeling volatilities and correlations between components of multivariate time series. An obvious drawback lies in that the number of parameters increases rapidly with the number of variables involved. This thesis tries to resolve the problem by using dimension reduction technique. We briefly review both factor models for dimension reduction and the MGARCH models including EWMA (Exponentially weighted moving-average model), DVEC(Diagonal VEC model), BEKK and CCC(Constant conditional correlation model). We create meaningful portfolios obtained after reducing dimension through statistical factor models and fundamental factor models and in turn these portfolios are applied to MGARCH. In addition, we compare portfolios by assessing MSE, MAD(Mean absolute deviation) and VaR(Value at Risk). Various financial time series are analyzed for illustration.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.12
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• pp.1208-1216
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• 2007

Turbomachinery such as turbines, pumps and compressors, which are installed in transportation systems, including aircrafts, ships, and space vehicles, etc., often perform crucial missions and are exposed to potential dangerous impact environments such as base-transferred shock forces. To protect turbomachinery from excessive shock forces, it may be needed to accurately analyze transient responses of their rotors, considering the dynamics of mount designs to be applied. In this study a generalized FE transient response analysis model, introducing relative displacements, is proposed to accurately predict transient responses of a flexible rotor-bearing system with mount systems to base-transferred shock forces. In the transient analyses the state-space Newmark method of a direct time integration scheme is utilized, which is based on the average velocity concept. Results show that for the identical mount systems considered, the proposed FE-based detailed flexible rotor model yields more reduced transient vibration responses to the same shocks than a conventional simple model, obtained by treating a rotor as concentrated lumped mass, equivalent spring and a damper or Jeffcott rotor model. Hence, in order to design a rotor-bearing system with a more compact light-weighted mount system, preparing against any potential excessive shock, the proposed FE transient response analysis model herein is recommended.

• The Korean Journal of Applied Statistics
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• v.34 no.4
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• pp.623-632
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• 2021

Through this study, we studied how to consider environment variables (such as temperatures, weekend, holiday) closely related to electricity demand, and how to consider the characteristics of Korea electricity demand. In order to conduct this study, Smoothing method, Seasonal ARIMA model and regression model with AR-GARCH errors are compared with mean absolute error criteria. The performance comparison results of the model showed that the predictive method using AR-GARCH error regression model with environment variables had the best predictive power.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.2
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• pp.51-59
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• 2017

Due to the rapid change of global business environment, the growth of China's steel industry and the inflow of cheap products, domestic steel industry is faced on downward trend. The change of business paradigms from a quantitative growth to a qualitative product is needed in this steel industry. In this environment, it is very important for domestic steel distribution companies to secure their competitiveness by selecting good supply companies through a efficient procurement strategy and effective method. This study tried to find out the success factors of steel distribution industry based on survey research from experts. Weighted values of each factors were found by using AHP (analytic hierarchy process) analysis. The weighted values were applied to DEA(data envelopment analysis) model and eventually the best steel supply company were selected. This paper used 29 domestic steel distribution firms for case example and 5 steps of decision process to select good vendors were suggested. This study used quality, price, delivery and finance as a selection criteria. Using this four criterions, nine variable were suggested. Which were product diversity, base price, discount, payment position, average delivery date, urgency order responsibility and financial condition. These variables were used as a output variable of DEA. Sales and facilities were used as an input variable. Pairwise comparison was conducted using these variables. The weighted value calculated by AHP pairwise comparison were used for DEA analysis. Through the analysis of DEA efficiency process, good DMU (decision making unit) were recommended as a steel supply company. The domestic case example was used to show the effectiveness of this study.

• Journal of the Korean Operations Research and Management Science Society
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• v.38 no.2
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• pp.75-93
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• 2013

In applying Markowitz's portfolio selection model to the stock market, we developed a comprehensive investment decision-making framework including key inputs for portfolio theory (i.e., individual stocks' expected rate of return and covariance) and minimum required expected return. For estimating the key inputs of our decision-making framework, we utilized an exponentially weighted moving average (EWMA) which places more emphasis on recent data than the conventional simple moving average (SMA). We empirically analyzed the investment results of the decision-making framework with the same 15 stocks in Samsung Group Funds found in the Korean stock market between 2007 and 2011. This five-year investment horizon is marked by global financial crises including the U.S. subprime mortgage crisis, the collapse of Lehman Brothers, and the European sovereign-debt crisis. We measure portfolio performance in terms of rate of return, standard deviation of returns, and Sharpe ratio. Results are compared with the following benchmarks : 1) KOSPI, 2) Samsung Group Funds, 3) Talmudic portfolio based on the na$\ddot{i}$ve 1/N rule, and 4) Markowitz's model with SMA. We performed sensitivity analyses on all the input parameters that are necessary for designing an investment decision-making framework : smoothing constant for EWMA, minimum required expected return for the portfolio, and portfolio rebalancing period. In conclusion, appropriate use of the comprehensive investment decision-making framework based on the Markowitz's model integrated with EWMA proves to achieve outstanding performance compared to the benchmarks.