• Journal of Advanced Navigation Technology
• /
• v.4 no.2
• /
• pp.162-170
• /
• 2000

Maneuvering targets are difficult for the Kalman filter to track since the target model of tracking filter might not fit the real target trajectory and the statistical characteristics of the target maneuver are unknown in advance. In order to track such a wildly maneuvering target, several schemes had been proposed and improved the tracking performance in some extent. In this paper a Kalman filter-based scheme is proposed for maneuvering target tracking. The proposed scheme estimates the target acceleration input vector directly from the feature of maneuvering target trajectories and updates the simple Kalman tracker by use of the acceleration estimates. Simulation results for various target profiles are analyzed for a comparison of the performances of our proposed scheme with that of conventional trackers.

• The Korean Journal of Applied Statistics
• /
• v.21 no.5
• /
• pp.855-866
• /
• 2008

Recently many small area estimation methods using the lattice data analysis have been studied and known that they have good performances. In the case of using the lattice data which is mainly used for small area estimation, the choice of better neighborhood information system is very important for the efficiency of the data analysis. Recently Lee and Shin (2008) compared and analyzed some neighborhood information systems based on GIS methods. In this paper, we evaluate the effect of various neighborhood information systems which were suggested by Lee and Shin (2008). For comparison of the estimators, MSE, Coverage, Calibration, Regression methods are used. The number of unemployment in Economic Active Population Survey(2001) is used for the comparison.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.2
• /
• pp.130-135
• /
• 2004

This paper presents a new design methods of the short-term load forecasting system (STLFS) using the data mining. The structure of the proposed STLFS is divided into two parts: the Takagi-Sugeno (T-S) fuzzy model-based classifier and predictor The proposed classifier is composed of the Gaussian fuzzy sets in the premise part and the linearized Bayesian classifier in the consequent part. The related parameters of the classifier are easily obtained from the statistic information of the training set. The proposed predictor takes form of the convex combination of the linear time series predictors for each inputs. The problem of estimating the consequent parameters is formulated by the convex optimization problem, which is to minimize the norm distance between the real load and the output of the linear time series estimator. The problem of estimating the premise parameters is to find the parameter value minimizing the error between the real load and the overall output. Finally, to show the feasibility of the proposed method, this paper provides the short-term load forecasting example.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.1
• /
• pp.153-161
• /
• 2017

Branching processes which is used for epidemic dispersion as stochastic process model have advantages to estimate parameters by real data. We have to estimate both mean and dispersion parameter in order to use the negative binomial distribution as an offspring distribution on branching processes. In existing studies on biology and epidemiology, it is estimated using maximum-likelihood methods. However, for most of epidemic data, it is hard to get the best precision of maximum-likelihood estimator. We suggest a Bayesian inference that have good properties of statistics for small-sample. After estimating dispersion parameter we modelled the posterior distribution for 2015 Korea MERS cases. As the result, we found that the estimated dispersion parameter is relatively stable no matter how we assume prior distribution. We also computed extinction probabilities on branching processes using estimated dispersion parameters.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
• /
• 2000.10a
• /
• pp.79-83
• /
• 2000

A sliding mode fuzzy control (SMFC) with disturbance estimator is applied to design a controller for the third generation benchmark problem on an wind-excited building. A distinctive feature in vibration control of large civil infrastructure is the existence of large disturbances, such as wind, earthquake, and sea wave forces. Those disturbances govern the behavior of the structure, however, they cannot be precisely measured, especially for the case of wind-induced vibration control. Since the structural accelerations are measured only at a limited number of locations without the measurement of the wind forces, the structure of the conventional control may have the feed-back loop only. General structure of the SMFC is composed of a compensation part and a convergent part. The compensation part prevents the system diverge, and the convergent part makes the system converge to the sliding surface. The compensation part uses not only the structural response measurement but also the disturbance measurement, so the SMFC has a feed-back loop and a feed-forward loop. To realize the virtual feed-forward loop for the wind-induced vibration control, disturbance estimation filter is introduced. the structure of the filter is constructed based on an auto regressive model for the stochastic wind force. This filter estimates the wind force at each time instance based on the measured structural responses and the stochastic information of the wind force. For the verification of the proposed algorithm, a numerical simulation is carried out on the benchmark problem of a wind-excited building. The results indicate that the present control algorithm is very efficient for reducing the wind-induced vibration and that the performance indices improve as the filter for wind force estimation is employed.

• Proceedings of the KIEE Conference
• /
• 2008.07a
• /
• pp.75-76
• /
• 2008

본 논문에서는 한국형 에너지 관리 시스템의 계통 해석용 프로그램을 위한 공통 데이터 모델의 구축에 대해 다루었다. 공통 데이터 모델이란 다양한 어플리케이션이 공유하여 사용할 수 있는 계통 모델의 데이터베이스를 가리키며 본 논문에서는 토폴로지 프로세서(topology processor, TP), 상태추정(state estimator, SE), 급전원 조류계산(dispatcher power flow, DPF), 휴전계획(outage scheduler, OS), 부하 분포계수(bus load distribution factor, BLDF), 송전 손실 민감도 계수(transmission loss sensitivity factor, TLSF) 등을 위한 공통 모델에 대해 다루었다. 공통 모델의 구축을 위해 각 어플리케이션에서 필요한 정보를 수집하여 전력계통의 토폴로지 구조과 계통 설비를 모델링 하였다. 최종적으로 계층적(hierarchy) 구조와 비계층적(non-hierarchy) 구조로 나뉘어진 직접(direct) 및 간접(indirect) 인덱스 코드를 사용하여 데이터로의 빠른 접근이 가능한 실시간 데이터베이스 형태를 제시하였다.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.8
• /
• pp.2188-2195
• /
• 1999

This paper proposes a new call admission control scheme utilizing an inverse fuzzy vector quantizer(IFVQ) and neuralnet, which combines benefits of IFVQ and flexibilities of FCM(Fuzzy-C-Means) arithmetics, to decide whether a requested call not to be trained in learning phase to be connected or not. The system generates the estimated traffic pattern for the cell stream of a new call, using feasible/infeasible patterns in codebook, fuzzy membership values that represent the degree to which each pattern of codebook matches input pattern, and FCM arithmetics. The input to the NN is the vector consisted of traffic parameters which are the means and variances of the number of cells arriving in decision as to whether to accept or reject a new call depends on whether the NN is used for decision threshold(+0.5). This method is a new technique for call admission control using the membership values as traffic parameter which declared to CAC at the call set up stage, and this is valid for a very general traffic model in which the calls of a stream can belong to an unlimited number of traffic classes. Through the simulations, it is founded the performance of the suggested method outperforms compared to the conventional NN method.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.13 no.6
• /
• pp.403-410
• /
• 2008

This paper suggests a standstill estimator to accurately identify induction motor (IM) parameters necessary for the vector control. A mathematical model that faithfully represents the general skin effect is introduced. Then, two exciting signals with a different frequency are sequentially injected to track the parameters based on the skin effect of the rotor bar. Little knowledge of the unknown motor allows the proposed methodology to employ a closed-loop control of an injected current, rather than open-loop voltage injection approaches. Subsequently, this control scheme proactively prevents electrical accidents resulting from an inadequate open-loop voltage injection. We develop a specialized offline commissioning test to compensate the phase delay resulting from the drive, which significantly affects the precision of the IM parameters. The effectiveness of the identification technique is validated by means of experiments performed on the three different IMs.

• The Transactions of the Korea Information Processing Society
• /
• v.1 no.1
• /
• pp.14-22
• /
• 1994

This paper proposes two Bayes estimators and their evaluation algorithms of the software reliability at the end testing stage in the Smith's Bayesian software reliability growth model under the data prior distribution BE(a, b), which is more general than uniform distribution, as a class of prior information. We consider both a squared-error loss function and the Harris loss function in the Bayesian estimation procedures. We also compare the MSE performances of the Bayes estimators and their algorithms of software reliability using computer simulations. And we conclude that the Bayes estimator of software reliability under the Harris loss function is more efficient than other estimators in terms of the MSE performances as a is larger and b is smaller, and that the Bayes estimators using the beta prior distribution as a conjugate prior is better than the Bayes estimators under the uniform prior distribution as a noninformative prior when a＞b.

• Korean Journal of Health Education and Promotion
• /
• v.30 no.1
• /
• pp.65-81
• /
• 2013

Objectives: The present study was carried out to develop and evaluate comprehensive health care program to prevent infectious disease and promote health in child-care centers by Doctor of Korean medicine. Methods: A nonequivalent control group pretest-posttest design study was conducted on 568 children and 85 child care teacher at 12 child care facilities for 12 weeks from July to October 2012. The program was consist of management, education, screening under concepts of traditional preventive medicine, Yangsaeng and Chimibyeong. Children's medical utilization due to infectious disease and attendance means functional status were measured by reports from parents. The Difference in difference(DID) estimator was applied data analysis, and added Zero-inflated negative binomial regression model. Also, attitudes on the infection of teacher was measured and analyzed through t-test. Results: After the intervention, the total medical utilization due to infectious disease decreased, but not significantly. Total absence, early leave and lateness decreased significantly. But, Attitude on the infection of child care teacher was not changed. The parent's satisfaction showed positive overall. Conclusions: The intervention program may be effective in preventing infectious disease and managing health in child-care center partially. To measure long-term effect, long-term study improved is requested.