• Journal of the Korean Statistical Society
• /
• v.22 no.2
• /
• pp.259-269
• /
• 1993

A moving average model, LMA(q) and an autoregressive-moving average model, NLARMA(p, q), with Laplacian marginal distribution are constructed and their properties are discussed; Their autocorrelation structures are completely analogus to those of Gaussian process and they are partially time reversible in the third order moments. Finally, we study the mixing property of NLARMA process.

• Proceedings of the Korean Geotechical Society Conference
• /
• 1999.03a
• /
• pp.309-314
• /
• 1999

In this paper, an application of finite element procedure fur tunnel failure analysis has been studied. The numerical model is applied to the simulation of a series of plane strain laboratory tests on the small scale model of a shallow tunnel. By comparing experimental and numerical results some conclusions are drawn on the effectiveness of the numerical approach. The findings from these numerical experiments show relative differences in the pattern of failure behaviour for shallow tunnels.

• Journal of the Korean Statistical Society
• /
• v.36 no.2
• /
• pp.183-200
• /
• 2007

We consider a nonlinear autoregressive moving average model with nonlinear GARCH errors, and find sufficient conditions for the existence of a strictly stationary solution of three related time series equations. We also consider a geometric ergodicity and functional central limit theorem for a nonlinear autoregressive model with nonlinear ARCH errors. The given model includes broad classes of nonlinear models. New results are obtained, and known results are shown to emerge as special cases.

• Korean Journal of Hydrosciences
• /
• v.3
• /
• pp.105-113
• /
• 1992

Various modeling approaches to study a long term behavior of streamflow or groundwater storage have been conducted. In this study, a Multivariate AR (1) Model has been applied to generate monthly flows of the one key station which has historical flows using monthly flows of the three subordinate stations. The Model performance was examined using statistical comparisons between the historical and generated monthly series such as mean, variance, skewness. Also, the correlation coefficients (lag-zero, and lag-one) between the two monthly flows were compared. The results showed that the modeled generated flows were statistically similar to the historical flows.

• 제어로봇시스템학회:학술대회논문집
• /
• 1993.10a
• /
• pp.805-810
• /
• 1993

In this paper, we propose a compliance control scheme using a neurofuzzzy compliance model(NFCM). as a new control paradigm for telerobot systems. A NFCM, used as a compliance controller, is composed of a fuzzy compliance model(FCM), a neural network and a low pass filter. The NFCM is trained through a reinforcement learning algorithm, and then, can generate suitable compliant motion for a given task. A series of simulations have been performed to show applicability of the proposed algorithm send it is found that the NFCM can implement suitable compliant motion for a given task through the learning procedure.

• 제어로봇시스템학회:학술대회논문집
• /
• 1996.10b
• /
• pp.233-236
• /
• 1996

This paper describes a liner state-space model for a flexible stick balencer. The method employed to generate the model utilizes a separable formulation of assumed modes to represents the transverse displacement due to bending Lagrangian dynamics are applied to determine the kinetic and potential energies for the system. The resultant dynamic equations are then organized into a state space model and linearized using Taylor series expansion method. A minimum order observer is designed to estimate unmeasurable states.

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.4
• /
• pp.837-844
• /
• 2003

In this paper, we obtain the estimator of system reliability for the bivariate Pareto model with bivariate type 1 censored data. We obtain the estimators and approximated confidence intervals of the reliability for the parallel system based on likelihood function and the relative frequency, respectively. Also we present a numerical example by giving a data set which is generated by computer.

• Advances in Computational Design
• /
• v.5 no.3
• /
• pp.291-304
• /
• 2020

In this paper, we develop models to design the airfoil using Multilayer Feed-forward Artificial Neural Network (MFANN) and Support Vector Regression model (SVR). The aerodynamic coefficients corresponding to series of airfoil are stored in a database along with the airfoil coordinates. A neural network is created with aerodynamic coefficient as input to produce the airfoil coordinates as output. The performance of the models have been evaluated. The results show that the SVR model yields the lowest prediction error.

• 제어로봇시스템학회:학술대회논문집
• /
• 1986.10a
• /
• pp.641-642
• /
• 1986

We present a method for the estimation of intramuscular electromyographic(EMG) signals from the given surface EMG signals. This method is based on representing the surface EMG signal as an autoregressive(AR) time model with a delayed intramuscular EMG signal as an input. The parameters of the time series model that transforms the intramuscular signal to the surface signal are identified. The identified model is then used in estimating the intramuscular signal from the surface signal.

• Proceedings of the KIEE Conference
• /
• 2002.11d
• /
• pp.313-316
• /
• 2002

In this paper, we present an online scheme for parameter estimation of solar cell, based on the model adjustment technique and a genetic algorithm. The ideal diode model and the diode model with series and shunt resistor are used to estimate their parameters. Simulation works using field data in the form of a VI characteristic curve are carried out to demonstrate the effectiveness of the proposed method.