• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.252-254
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• 1992

This paper proposes a new algorithm that finds fuzzy control law of the system in which little knowledge has been known. In view or conventional fuzzy method, making control law needs the sense and the knowledge of the system which are provided by expert. But fuzzy control using proposed algorithm needs no expert for hating control law. After construction of the 1st order approximated ARMA model using input-output pairs, new defuzzification method is applied. The deduced rule is stored in fuzzy input space and updated by the proposed algorithm adaptively. To show the validity and effectiveness of proposed control method. simulation result is presented.

• Wind and Structures
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• v.18 no.3
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• pp.215-233
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• 2014

This paper presents a method to extract flutter derivatives of bridge decks based on a combination of the computational fluid dynamics (CFD), system simulations and system identifications. The incompressible solver adopts an Arbitrary Lagrangian-Eulerian (ALE) formulation with the finite volume discretization in space. The imposed sectional motion in heaving or pitching relies on exponential time series as input, with aerodynamic forces time histories acting on the section evaluated as output. System identifications are carried out to fit coefficients of the inputs and outputs of ARMA models, as to establish discrete-time aerodynamic models. System simulations of the established models are then performed as to obtain the lift and moment exerting on the sections to a sinusoidal displacement. It follows that flutter derivatives are identified. The present approaches are applied to a hexagon thin plate and a real bridge deck. The results are compared to the Theodorsen closed-form solution and those from wind tunnel tests. Satisfactory agreements are observed.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.6
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• pp.49-56
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• 2011

Grounding system insures a reference potential point for electric devices and also provides a low impedance path for fault currents or transient currents in the earth. The ground impedance as function of frequency is necessary for determining its performance since fault currents could contain a wide range of frequencies. In this paper, the grounding resistance, grounding impedance and transient grounding impedance are measured by using 3-point fall-of-potential method in order to analyse grounding characteristics of the copper and concrete rod grounding electrodes. An equivalent transfer function model of the ground impedance and transient grounding impedance are identified from the measured values by using ARMA method and evaluated by comparing the conventional grounding impedance.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.289-305
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• 1997

In this paper, design procedure and estimation of the double sampling plans are developed when the production process is examined in order and if it shows the dependence between the products. If a dependent process model can be simulated, the best sampling plans can be selected by using the special properties of the probability structure. The number of actual evaluations to find the plans can be reduced remarkably. The experimental study reveals that only small portion of the total exhaustive enumeration is needed. ARMA (1,1) time series models are given as numerical examples.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2968-2970
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• 2000

시계열(time series)이란 한 사상 또는 여러 사상에 대하여 시간의 흐름에 따라 일정한 간격으로 이들을 관측하여 기록한 자료를 말한다. 이러한 시계열은 어떠한 경제현상이나 자연현상에 관한 시간적 변화를 나타내는 역사적 계열(historical series)이므로 어느 한 시점에서 관측된 시계열자료는 그 이전까지의 자료들에 주로 의존하게 된다. 따라서 시계열분석을 통한 예측에서는 과거의 자료들을 분석하여 법칙성을 발견해서 이를 모형화하여 추정하고. 이 추정된 모형을 사용하여 미래에 관측될 값들을 예측하게 된다. 본 연구에서는 ARMA (p, q)모형 (autoregressive moving-average model)을 이용하여 시계열 데이터를 분석하며 계수의 추정에는 Levinson-Durbin 알고리듬과 Newton-Raphson Method를 이용한다.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.7
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• pp.257-266
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• 1985

A new method for the artificial beta cell which can be used to control the hyperglycemia in diabetic patients was represented. The relationship between the insulin infusion rate and the blood glucose concentration was described by the second order ARMA model, and the time varying parameters were identified by exponentially weighted least squares estimator. The design of controller was based on the pole assignment self tuning altorithm with discrete blood sampling and the constraints of input and output responsse rate were considered. The results of animal experiments show that this method may be a fruitful approach for regulating the blood glucose level. We expect that this device can be used as both therapeutic and research tools providing that its stability and reliability are improved a little more.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.141-141
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• 2022

Drought is a global phenomenon that affects almost all landscapes and causes major damages. Due to non-linear nature of contributing factors, drought occurrence and its severity is characterized as stochastic in nature. Early warning of impending drought can aid in the development of drought mitigation strategies and measures. Thus, drought forecasting is crucial in the planning and management of water resource systems. The primary objective of this study is to make improvement is existing drought forecasting techniques. Therefore, we proposed an improved version of Seasonal Autoregressive Integrated Moving Average (SARIMA) model (MD-SARIMA) for reliable drought forecasting with three years lead time. In this study, we selected four watersheds of Han River basin in South Korea to validate the performance of MD-SARIMA model. The meteorological data from 8 rain gauge stations were collected for the period 1973-2016 and converted into watershed scale using Thiessen's polygon method. The Standardized Precipitation Index (SPI) was employed to represent the meteorological drought at seasonal (3-month) time scale. The performance of MD-SARIMA model was compared with existing models such as Seasonal Naive Bayes (SNB) model, Exponential Smoothing (ES) model, Trigonometric seasonality, Box-Cox transformation, ARMA errors, Trend and Seasonal components (TBATS) model, and SARIMA model. The results showed that all the models were able to forecast drought, but the performance of MD-SARIMA was robust then other statistical models with Wilmott Index (WI) = 0.86, Mean Absolute Error (MAE) = 0.66, and Root mean square error (RMSE) = 0.80 for 36 months lead time forecast. The outcomes of this study indicated that the MD-SARIMA model can be utilized for drought forecasting.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.225-225
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• 2015

Drought events usually evolve slowly in time and their impacts generally span a long period of time. This indicates that the sequence of drought is not completely random. The Hidden Markov Model (HMM) is a probabilistic model used to represent dependences between invisible hidden states which finally result in observations. Drought characteristics are dependent on the underlying generating mechanism, which can be well modelled by the HMM. This study employed a HMM with Gaussian emissions to fit the Standardized Precipitation Index (SPI) series and make multi-step prediction to check the drought characteristics in the future. To estimate the parameters of the HMM, we employed a Bayesian model computed via Markov Chain Monte Carlo (MCMC). Since the true number of hidden states is unknown, we fit the model with varying number of hidden states and used reversible jump to allow for transdimensional moves between models with different numbers of states. We applied the HMM to several stations SPI data in South Korea. The monthly SPI data from January 1973 to December 2012 was divided into two parts, the first 30-year SPI data (January 1973 to December 2002) was used for model calibration and the last 10-year SPI data (January 2003 to December 2012) for model validation. All the SPI data was preprocessed through the wavelet denoising and applied as the visible output in the HMM. Different lead time (T= 1, 3, 6, 12 months) forecasting performances were compared with conventional forecasting techniques (e.g., ANN and ARMA). Based on statistical evaluation performance, the HMM exhibited significant preferable results compared to conventional models with much larger forecasting skill score (about 0.3-0.6) and lower Root Mean Square Error (RMSE) values (about 0.5-0.9).

• The Journal of the Korea Contents Association
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• v.6 no.2
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• pp.34-43
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• 2006

This paper shows modeling methods for VBR video trace. It is well known that VBR video trace is characterized as longterm correlated and highly intermittent burst data. To analyze this, we attempt to model it using neural network with auxiliary linear structures derived from residual threshold. For testing purpose, we generate VBR video trace from chaotic nonlinear function combined with the geometric random noise. The modeling result of the generated data shows that the attempted method represents more accurately than the traditional neural network. However, we also found that combining hRU to the attempted modeling method can yield a closer agreement to statistical features of the generated data than the attempted modeling method alone.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.571-576
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• 1994

In recent years, ultrasonic has been widely applied in measurement and industrial fields and its application range has been expanded as a result of continuous research and development. Wire Bonding Machine, an instrument fabricating semi-conductor, makes use of ultrasonic bonding method. In order to improve the currently used wire bonding machine using ultrasonic energy, technical accumulation is needed steadily through development of exciting device of ultrasonic composed of piezoelectic vibrator and horn. This study investigates the design conditions affecting the dynamic characteristics through the theoretical and experimental analysis of piezoelectric vibrator and horn, The study conducts separately the system identification of piezoelectric vibrator in time domain and the modal analysis of horn in frequency domain. In theoretical model, the integrated modeling is conducted via a combination of dynamic identification of piezoelectric vibrator and theoretical analysis of horn. Hence comparison is made for theoretical and experimental results of the dynamic characteristics of the ultrasonic transducer composed of piezoelectric vibrator and horn. Form the results of this study we develop the design technique of ultrasonic transducer using dynamic characteristic analysis and propose the possibility of ultrasonic welding considering the optimal condition of the natural frequency and vibration mode of horn.