• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.201-207
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• 2023

In this paper, we propose an optimal model for mid to long-term price prediction of agricultural products using LGBM, MLP, LSTM, and GRU to compare and analyze the three strategies of the Multi-Step Time Series. The proposed model is designed to find the optimal combination between the models by selecting methods from various angles. Prior agricultural product price prediction studies have mainly adopted traditional econometric models such as ARIMA and LSTM-type models. In contrast, agricultural product price prediction studies related to Multi-Step Time Series were minimal. In this study, the experiment was conducted by dividing it into two periods according to the degree of volatility of agricultural product prices. As a result of the mid-to-long-term price prediction of three strategies, namely direct, hybrid, and multiple outputs, the hybrid approach showed relatively superior performance. This study academically and practically contributes to mid-to-long term daily price prediction by proposing an effective alternative.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.279-285
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• 2002

In this paper we consider the problem of testing for structural changes in ARIMA models based on a cusum test. In particular, the proposed test procedure is applicable to testing for a change of the status of time series from stationarity to nonstationarity or vice versa. The idea is to transform the time series via differencing to make stationary time series. We propose a graphical method to identify the correct order of differencing.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.151-152
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• 2005

IGARCH and Stochastic Volatility Model(SVM, for short) have frequently provided useful approximations to the real aspects of financial time series. This article is concerned with modeling various Korean financial time series using both IGARCH and Stochastic Volatility Models. Daily data sets with sample period ranging from 2000 and 2004 including KOSPI, KOSDAQ and won-dollar exchange rate are comparatively analyzed using IGARCH and SVM.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10a
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• pp.332-337
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• 1988

A digital series-feedback compensator algorithm for tracking time-varying signal is presented. The series-feedback compensator is composed of one closed loop pole / zero cancellation compensator and one desired-input generator. This algorithm is applied to nonlinear hydraulic position control system. The hydraulic servo system is modelled as a second order linear model and cancellation compensator is modelled from it. The desired input generator is inserted to reduce modelling error. Digital computer simulation output using this control method is present and the usefulness of this control algorithm for nonlinear hydraulic system is verified.

• Journal of Mechanical Science and Technology
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• v.17 no.2
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• pp.288-295
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• 2003

A preliminary series design of compressors for a two-stage centrifugal chiller is suggested. Six groups of hydrodynamically similar compressors, ranging from 233RT to 1,200RT, are introduced. Flow rates, impeller diameters, and wheel speeds for each group are determined from hydrodynamic similarity to share impellers of adjacent groups. It is expected that these compressors can have the same performance and efficiency from the smallest model to the largest one.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.835-841
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• 2005

IGARCH and Stochastic Volatility Model(SVM, for short) have frequently provided useful approximations to the real aspects of financial time series. This article is concerned with modeling various Korean financial time series using both IGARCH and stochastic volatility models. Daily data sets with sample period ranging from 2000 and 2004 including KOSPI, KOSDAQ and won-dollar exchange rate are comparatively analyzed using IGARCH and SVM.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.43-48
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• 2005

We consider the problem of testing for parameter changes in time series models based on a cusum test. Although the test procedure is well-established for the mean and variance in time series models, a general parameter case has not been discussed in the literature. Therefore, here we develop a cusum test for parameter change in a more general framework. As an example, we consider the change of the parameters in an RCA(1) model and that of the autocovariances of a linear process. We also consider the variance change test for unstable models with unit roots and GARCH models.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.6
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• pp.376-382
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• 1988

A small-signal low-frequency disturbance of the input line affects the regulated-output voltage of the series resonant converter. To mitigate the detrimental effect, the output feedback PI-controller is employed. Small-signal linear models are represented to characterize the closed loop series resonant converter system. Design equations for the PI-controller which satisfy stability and percent ripple conditions are derived from the closed-loop linear model. Experimental results are presented which show excellent correlation with theory.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.219-226
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• 2004

In this paper, we consider two-components system which the lifetimes have a bivariate Weibull distribution with bivariate random censored data. Here the bivariate censoring times are independent of the lifetimes of the components. We obtain estimators and approximated confidence intervals for the reliability of series system based on likelihood function and relative frequency, respectively. Also we present a numerical study.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.7 no.10
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• pp.47-51
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• 1984

In many forecasting problem, there is little or no useful historical information available at the time the initial forecast is required, The propose of this paper is study on Bayesian Method in forecasting. I : Introduction. II : Bayesian estimation. III : Constant Model. IV : General time series Models. V : Conclusion. The Bayesian procedure are then used to revise parameter estimates when time series information is available, in this paper we give a general description of the bayesian approach and demonstrate the methodology with several specific cases.