• 제어로봇시스템학회논문지
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• 제2권2호
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• pp.121-126
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• 1996

The hydrodynamic coefficients estimation (HCE) is important to design the autopilot and to predict the maneuverability of an underwater vehicle. In this paper, a system identification is proposed for an HCE of an underwater vehicle. First, we attempt to design the HCE algorithm which is insensitive to initial conditions and has good convergence, and which enables the estimation of the coefficents by using measured displacements only. Second, the sensor and measurement system which gauges the data from the full scale trials is constructed and the data smoothing algorithm is also designed to filter the noise due to irregular fluid flow without changing the data characteristics itself. Lastly the hydrodynamic coefficients are estimated by applying the measured data of full scale trials to the developed algorithm, and the estimated coefficients are verified by full scale trials.

• Journal of the Korean Data and Information Science Society
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• 제16권3호
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• pp.567-580
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• 2005

It is usually assumed that asset returns in the stock market are normally distributed. However, analyses of real data show that the distribution tends to be skewed and to have heavier tails than those of the normal distribution. In this paper, we investigate the method of estimating the value at risk(VaR) of stock returns. The VaR is computed by using the transformation and back-transformation method. The analysis of KOSPI and KOSDAQ data shows that the proposed estimation outperformed that under the normal assumption.

• 산업경영시스템학회지
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• 제34권1호
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• pp.42-51
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• 2011

Poisson model and Gamma-Poisson model are popularly used to analyze statistical behavior from defective data. The methods are based on binary criteria, that is, good or failure. However, manufacturing industries prefer polytomous criteria for classifying manufactured products due to flexibility of marketing. In this paper, I introduce two multivariate Gamma-Poisson(MGP) models and estimation methods of the parameters in the models, which are able to handle polytomous data. The models and estimators are verified on defective pixels of LCD manufacturing. Experimental results show that both the independent MGP model and the multinomial MGP model have excellent performance in terms of mean absolute deviation and the choice of method depends on the purpose of use.

• 한국정밀공학회지
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• 제17권2호
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• pp.114-120
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• 2000

Fossil power plant availability is significantly affected by gradual degradations of equipment as operation of the plant continues. It is quite important to determine whether or not to replace some equipment and when to replace the equipment. Performance calculation and analysis can provide the information. Robustness in the performance calculation can be increased by using verification ＆ validation of measured input data. We suggest new algorithm in which estimation relation for validated measurement can be obtained using correlation between measurements. Input estimation model is obtained using design data and acceptance measurement data of domestic 16 fossil power plant. The model consists of finding mostly correlated state variable in plant state and mapping relation based on the model and current state of power plant.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
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• pp.406-408
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• 2006

Various geological thematic maps such as grain size or ground water level maps have been generated by interpolating sparsely sampled ground survey data. When there are sampled data at a limited number of locations, to use secondary information which is correlated to primary variable can help us to estimate the attribute values of the primary variable at unsampled locations. This paper applies two multivariate geostatistical algorithms to integrate remote sensing imagery with sparsely sampled ground survey data for spatial estimation of grain size: simple kriging with local means and kriging with an external drift. High-resolution IKONOS imagery which is well correlated with the grain size is used as secondary information. The algorithms are evaluated from a case study with grain size observations measured at 53 locations in the Baramarae beach of Anmyeondo, Korea. Cross validation based on a one-leave-out approach is used to compare the estimation performance of the two multivariate geostatistical algorithms with that of traditional ordinary kriging.

• Journal of the Korean Statistical Society
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• 제25권4호
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• pp.529-544
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• 1996

This paper deals with the problem of estimating the autoregressive random coefficient of a first-order random coefficient autoregressive time series model applied to panel data of time series. The autoregressive random coefficients across individual units are assumed to be a random sample from a truncated normal distribution with the space (-1, 1) for stationarity. The estimates of random coefficients are obtained by an empirical Bayes procedure using the estimates of model parameters. Also, a Monte Carlo study is conducted to support the estimation procedure proposed in this paper. Finally, we apply our results to the economic panel data in Liu and Tiao(1980).

• 대한전기학회:학술대회논문집
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• 대한전기학회 1989년도 추계학술대회 논문집 학회본부
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• pp.186-190
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• 1989

A Study for Bad Data Processing in state estimation by a Neural Network is presented. State estimation is the process of assigning a value to an unknown system state variable based on measurement from that system according to some criteria. In this case, the ability to detect and identify bad measurements is extremely valuable, and much time in oder to achieve the state estimation is needed. This paper proposed new bad data processing using Neural Network in order to settle it. The concept of neural net is a parallel distributed processing. In this paper, EBP (Error Back Propagation) algorithm based on three layered feed forward network is used.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 2002년도 추계 학술발표회 논문집
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• pp.28-34
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• 2002

The b-value in the magnitude-frequency relationship logN(m) = $\alpha$ - bmwhere N(m) is the number of earthquakes exceeding magnitude m, is important seismicity parameter In hazard analysis. Estimation of the b-value for earthquake data observed on KSRS array network is done employing the maximum likelihood technique. Assuming the whole Korea Peninsula as a single seismic source area, the b-value is computed at 0.9. The estimation for KMA earthquake data is also similar to that. Since estimate is a function of minimum magnitude, we can inspect the completeness of earthquake catalog in the fitting process of b-value. KSRS and KMA data lists are probably incomplete for magnitudes less than 2.0 and 3.0, respectively. Examples from probabilistic seismic hazard assessment calculated for a range of b-value show that the small change of b-value has seriously effect on the prediction of ground motion.

• 센서학회지
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• 제5권4호
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• pp.57-70
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• 1996

Motion can be estimated continuously from each sensor through the analysis of the instantaneous states of an object. This paper is aimed to introduce a method to estimate the general 3D motion of a planar object from the instantaneous states of an object using multi-sensor data fusion. The instantaneous states of an object is estimated using the linear feedback estimation algorithm. The motion estimated from each sensor is fused to provide more accurate and reliable information about the motion of an unknown planar object. We present a fusion algorithm which combines averaging and deciding. With the assumption that the motion is smooth, the approach can handle the data sequences from multiple sensors with different sampling times. Simulation results show proposed algorithm is advantageous in terms of accuracy, speed, and versatility.

• 지역연구
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• 제11권2호
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• pp.1-17
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• 1995

Regional production structres are investigated through an estimation of three-input(labor, capital and material) translog cost function. The estimation uses the pooled data in which time series data of 1970-1990 are combined with cross-sectional data corresponding to firm sizes. The empirical finding are the following: (1) the factors are Allen substitutes each otner in general except Pusan and a couple of regionss, and (2) estimates are very small in its absolute value irrespective of the regions. The low elasticity estimates of this study implies that substitytability among the three inputs are very weak in the regional manufacturing production compared to that in the national production. Seoul-Kyungki metropolitan area produces not only the smallest elasticities but relatively stable estimates without much fluctuation between the sub-regions of the area.