• Journal of Power Electronics
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• 제18권2호
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• pp.445-455
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• 2018

A novel algorithm is proposed to regulate the neutral point potential in neutral point clamped three-level inverters. Oscillations of the neutral point potential and an unbalanced dc-link voltage cause distortions of the output voltage. Large capacitors, which make the application costly and bulky, are needed to eliminate oscillations. Thus, the algorithm proposed in this paper utilizes the finite-control-set model predictive control and the multistage medium vector to solve these issues. The proposed strategy consists of a two-step prediction and a cost function to evaluate the selected multistage medium vector. Unlike the virtual vector method, the multistage medium vector is a mixture of the virtual vector and the original vector. In addition, its amplitude is variable. The neutral point current generated by it can be used to adjust the neutral point potential. When compared with the virtual vector method, the multistage medium vector contributes to decreasing the regulation time when the modulation index is high. The vectors are rearranged to cope with the variable switching frequency of the model predictive control. Simulation and experimental results verify the validity of the proposed strategy.

• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.235-247
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• 1993

The predictive density function of a potential future observation and its first four moments are obtained in this paper to study the effects of a non-normal prior of the unknown mean of a normal population. The derived predictive density function is modified to study changes in utility curves, used to choose the optimum treatment from a given set of treatments, at a given level of stimulus due to slight deviations from normality of the prior distribution. Numerical illustrations are provided to exhibit some effectsl.

• 한국항공우주학회지
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• 제33권11호
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• pp.48-56
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• 2005

Predictive 필터는 Kalman 필터의 단점을 보완하고 모델 오차를 동시에 추정할수 있는 최근에 제시된 기법이다. 한 단계 앞의 추정 오차를 최소화하기 위한 최적화된 필터의 형태가 Predictive 필터이다. 본 필터의 주요 장점은 상태변수와 함께 모델오차를 파악할 수 있다는데 있다. 본 연구에서는 Predictive 필터를 이용한 인공위성의 자세추정 내용을 소개하도록 한다. 기존에 제시된 Predictive 필터 이론을 적용하여 자이로 바이어스 신호를 추정할수 있는 수식을 유도하고 또한 벡터 관측 정보를 이용한 자세추정 결과를 소개하도록 한다. 본 연구결과를 통해 향후 Predictive 필터의 확장 가능성을 예상할 수 있다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.1068-1071
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• 1993

An algorithm of fuzzy predictive sliding control is proposed to design a jet engine control system. Sliding control using predictive scheme is adopted to compensate the time delay of fuel injector. Fuzzy rule-base is also introduced to adjust the command input for suppressing the surge. The potential of the proposed algorithm is shown through simulations utilizing a typical engine-only model.

• 지구물리와물리탐사
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• 제23권3호
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• pp.149-156
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• 2020

복잡하고 다양한 광상 생성 과정과 부존 위치의 심부화로 인하여 광물자원 탐사의 효율을 높일 수 있는 예측탐사의 필요성이 점차 높아지고 있다. 최근의 머신러닝 기법의 활용성 증가와 광역 지질 데이터베이스의 구축 상황을 고려하면, 예측탐사의 기반인 광상 배태 가능성 평가 기술의 신뢰도는 점차 높아질 것으로 예상된다. 이번 연구에서는 심층신경망을 이용하여 화성암과 단층 및 자력탐사 정보의 광화 인자로의 활용 가능성을 확인하였다. 지질 정보의 수치화 기법으로 단층, 화성암, 자력 정보를 입력 자료로 구성하여 0.9 이상의 정확도를 가지며 예측 값이 안정적으로 수렴하는 금속 광상 예측 모델을 구축할 수 있었다. 이 기술은 추후 정밀한 지질 조사 결과와 물리탐사 정보가 확보된다면, 광화대 규모에서의 예측 탐사에도 활용할 수 있을 것으로 기대된다. 또한, 이 연구를 통해 지하의 화성암 정보를 제공하는 자력자료를 활용할 경우 지표의 화성암 정보를 보완하여 보다 높은 성능의 모델을 구축할 수 있는 것으로 확인되었다. 즉, 단순히 많은 자료를 융합하는 것 보다는 광체 성인과의 지질학적 상관관계를 고려하여 입력 자료를 구성하는 것이 보다 중요하다.

• Journal of Power Electronics
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• 제13권6호
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• pp.1016-1023
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• 2013

Predictive current control offers the potential for achieving more precise current control with a minimum of distortion and harmonic noise. However, the predictive method is difficult to implement and has a greater computational burden. This paper introduces a theoretical analysis and experimental verification for an improved predictive current control technique applied to single phase grid connected voltage source inverters (VSI). The proposed technique has simple calculations. An ATmega1280 microcontroller board is used to implement the proposed technique for a simpler and cheaper control system. To enhance the current performance and to obtain a minimum of current THD, an improved tri-level PWM switching strategy is proposed. The proposed switching strategy uses six operation modes instead of four as in the traditional strategy. Simulation results are presented to demonstrate the system performance with the improved switching strategy and its effect on current performance. The presented experimental results verify that the proposed technique can be implemented using fixed point 8-bit microcontroller to obtain excellent results.

• Journal of Preventive Medicine and Public Health
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• 제39권5호
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• pp.433-437
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• 2006

Objectives: The aim of this study is to develop a methodology for estimating a nationwide statistic for hernia operations with using the claim database of the Korea Health Insurance Cooperation (KHIC). Methods: According to the insurance claim procedures, the claim database was divided into the electronic data interchange database (EDI_DB) and the sheet database (Paper_DB). Although the EDI_DB has operation and management codes showing the facts and kinds of operations, the Paper_DB doesn't. Using the hernia matched management code in the EDI_DB, the cases of hernia surgery were extracted. For drawing the potential cases from the Paper_DB, which doesn't have the code, the predictive model was developed using the data mining technique called SEMMA. The claim sheets of the cases that showed a predictive probability of an operation over the threshold, as was decided by the ROC curve, were identified in order to get the positive predictive value as an index of usefulness for the predictive model. Results: Of the claim databases in 2004, 14,386 cases had hernia related management codes with using the EDI system. For fitting the models with applying the data mining technique, logistic regression was chosen rather than the neural network method or the decision tree method. From the Paper_DB, 1,019 cases were extracted as potential cases. Direct review of the sheets of the extracted cases showed that the positive predictive value was 95.3%. Conclusions: The results suggested that applying the data mining technique to the claim database in the KHIC for estimating the nationwide surgical statistics would be useful from the aspect of execution and cost-effectiveness.

• Journal of Electrical Engineering and Technology
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• 제10권1호
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• pp.227-242
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• 2015

This paper proposes a weighting factor optimization method in predictive control algorithm for torque ripple reduction in an induction motor fed by an indirect matrix converter (IMC). In this paper, the torque ripple behavior is analyzed to validate the proposed weighting factor optimization method in the predictive control platform and shows the effectiveness of the system. Therefore, an optimization method is adopted here to calculate the optimum weighting factor corresponds to minimum torque ripple and is compared with the results of conventional weighting factor based predictive control algorithm. The predictive control algorithm selects the optimum switching state that minimizes a cost function based on optimized weighting factor to actuate the indirect matrix converter. The conventional and introduced weighting factor optimization method in predictive control algorithm are validated through simulations and experimental validation in DS1104 R&D controller platform and show the potential control, tracking of variables with their respective references and consequently reduces the torque ripple.

• 한국지형학회지
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• 제24권3호
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• pp.105-118
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• 2017

The debris slope landforms which are existent in Korean mountains is generally on the steep slopes and mostly covered by vegetation, it is difficult to investigate the landform. Therefore a scientific method is required to come up with an effective field investigation plan. For this purpose, the use of Remote Sensing and GIS technologies for a spatial analysis is essential. This study has extracted the potential area of debrisslope landform formation using Fuzzy set and Bayesian Predictive Discriminate Model as mathematical data integration methods. The first step was to obtain information about debris locations and their related factors. This information was verified through field investigation and then used to build a database. In the second step, the map that zoning the study area based on the degree of debris formation possibility was generated using two modeling methods, and then cross validation technique was applied. In order to quantitatively analyze the accuracy of two modeling methods, the calculated potential rate of debrisformation within the study area was evaluated by plotting SRC(Success Rate Curve) and calculating AUC(Area Under the Curve). As a result, the prediction accuracy of Fuzzy set model wes 83.1% and Bayesian Predictive Discriminate Model wes 84.9%. It showed that two models are accurate and reliable and can contribute to efficient field investigation and debris landform management.

• International journal of advanced smart convergence
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• 제12권3호
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• pp.221-232
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• 2023

Recently, due to the expansion of the logistics industry, demand for logistics automation equipment is increasing. The modern logistics industry is a high-tech industry that combines various technologies. In general, as various technologies are grafted, the complexity of the system increases, and the occurrence rate of defects and failures also increases. As such, it is time for a predictive maintenance model specialized for logistics automation equipment. In this paper, in order to secure the operational reliability of the ICT/Cold-Chain Unmanned Storage, a predictive maintenance system was implemented based on the LSTM model. In this paper, a server for data management, such as collection and monitoring, and an analysis server that notifies the monitoring server through data-based failure and defect analysis are separately distinguished. The predictive maintenance platform presented in this paper works by collecting data and receiving data based on RabbitMQ, loading data in an InMemory method using Redis, and managing snapshot data DB in real time. The predictive maintenance platform can contribute to securing reliability by identifying potential failures and defects that may occur in the operation of the ICT/Cold-Chain Unmanned Storage in the future.