• 한국지하수토양환경학회지:지하수토양환경
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• 제21권6호
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• pp.179-191
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• 2016

In addition to the measurement of the concentration of soil contaminants, the new idea of indicative parameters was proposed to validate the remedial works through the monitoring for the changes of soil characteristics after applying the clean up technologies. The parameters like CFU (colony forming unit), pH and soil texture were recommended as indicative parameters for land farming. In case of soil washing, water content and the particle size distribution of the sludge were recommended as indicative parameters. The sludge is produced through the particle separation process in soil washing and it is usually treated as a waste. The parameters like water content, organic matter content, CEC (cation exchange capacity) and CFU were recommended as indicative parameters for the low temperature thermal desorption method. Besides the indicative parameter, sampling methods in stock pile and the optimal minimum amount of composite soil sample were proposed. The rates of sampling error in regular grid, zigzag, four bearing, random grid methods were 17.3%, 17.6%, 17.2% and 16.5% respectively. The random grid method showed the minimum sampling error among the 4 kinds of sampling methods although the differences in sampling errors were very little. Therefore the random grid method was recommended as an appropriate sampling method in stock pile. It was not possible to propose a value of optimal minimum amount of composite soil sample based on the real analytical data due to the dynamic variation of $CV_{fund{\cdot}error}$. Instead of this, 355 g of soil was recommended for the optimal minimum amount of composite soil sample under the assumption of ISO 10381-8.

• Communications for Statistical Applications and Methods
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• 제23권1호
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• pp.47-55
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• 2016

Stratified cluster sampling has been widely used for effective parameter estimations due to reductions in time and cost. The probability proportional to size (PPS) sampling method is used when the number of cluster element are significantly different. However, simple random sampling (SRS) is commonly used for simplicity if the number of cluster elements are almost the same. Also it is known that the ratio estimator produces a good performance when the total number of population elements is known. However, the two stage cluster estimator should be used if the total number of elements in population is neither known nor accurate. In this study we suggest a composite estimator by combining the ratio estimator and the two stage cluster estimator to obtain a better estimate under a certain population circumstance. Simulation studies are conducted to compare the superiority of the suggested estimator with two other estimators.

• Journal of Electrical Engineering and Technology
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• 제12권5호
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• pp.1743-1753
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• 2017

Since there are multiple random variables in the probabilistic load flow (PLF) calculation of distribution system containing distributed generation (DG) and electric vehicle charging load (EVCL), a Monte Carlo method based on composite sampling method is put forward according to the existing simple random sampling Monte Carlo simulation method (SRS-MCSM) to perform probabilistic assessment analysis of voltage quality of distribution system containing DG and EVCL. This method considers not only the randomness of wind speed and light intensity as well as the uncertainty of basic load and EVCL, but also other stochastic disturbances, such as the failure rate of the transmission line. According to the different characteristics of random factors, different sampling methods are applied. Simulation results on IEEE9 bus system and IEEE34 bus system demonstrates the validity, accuracy, rapidity and practicability of the proposed method. In contrast to the SRS-MCSM, the proposed method is of higher computational efficiency and better simulation accuracy. The variation of nodal voltages for distribution system before and after connecting DG and EVCL is compared and analyzed, especially the voltage fluctuation of the grid-connected point of DG and EVCL.

• Korean Chemical Engineering Research
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• 제52권5호
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• pp.564-573
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• 2014

이 연구는 벤젠과 프로필렌의 기상반응을 통해 쿠멘을 생산하는 쿠멘 생산 공정의 경제성 최적화에 대한 것이다. 최적화의 목적함수는 제품 판매 이득에서 자본비용, 유틸리티 비용, 원료 비용을 뺀 연간 조업이득이고, 설계변수는 6개이다. 설계변수의 변화에 따른 조업이득의 계산을 위해 Unisim Design과 Matlab을 연동하였다. 최적화는 3단계로 수행되었다. 설계변수를 샘플링한 후 조업이득 데이터를 얻고, 이 데이터로부터 설계변수와 조업이득의 관계를 추정 모델로 표현하고, 이 모델을 이용하여 최적화하였다. 추정모델로는 반응표면법에서 사용되는 2차 회귀 다항식과 비선형 모델인 support vector regression을 비교하였다. 설계변수의 샘플링 방법으로는 중심합성계획과 Hammersley 순차 추출법을 비교하였다. 각각 얻어진 모델을 이용한 최적화 결과, 추정방법으로는 SVR이, 샘플링 방법은 Hammersley 순차추출법이 더 정확하였다. 최적화된 조업이득은 연간 17.96 MM$로, 기준 조건에서의 연간 16.04 MM$에 비해 12% 증가하였다.

• 산업경영시스템학회지
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• 제45권4호
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• pp.233-239
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• 2022

The injection molding process is a process in which thermoplastic resin is heated and made into a fluid state, injected under pressure into the cavity of a mold, and then cooled in the mold to produce a product identical to the shape of the cavity of the mold. It is a process that enables mass production and complex shapes, and various factors such as resin temperature, mold temperature, injection speed, and pressure affect product quality. In the data collected at the manufacturing site, there is a lot of data related to good products, but there is little data related to defective products, resulting in serious data imbalance. In order to efficiently solve this data imbalance, undersampling, oversampling, and composite sampling are usally applied. In this study, oversampling techniques such as random oversampling (ROS), minority class oversampling (SMOTE), ADASYN(Adaptive Synthetic Sampling), etc., which amplify data of the minority class by the majority class, and complex sampling using both undersampling and oversampling, are applied. For composite sampling, SMOTE+ENN and SMOTE+Tomek were used. Artificial neural network techniques is used to predict product quality. Especially, MLP and RNN are applied as artificial neural network techniques, and optimization of various parameters for MLP and RNN is required. In this study, we proposed an SA technique that optimizes the choice of the sampling method, the ratio of minority classes for sampling method, the batch size and the number of hidden layer units for parameters of MLP and RNN. The existing sampling methods and the proposed SA method were compared using accuracy, precision, recall, and F1 Score to prove the superiority of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.468-471
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• 1997

In this paper, we investigate the time-sampling effects on the digital implementation of singular perturbation based STT autopilot with excellent performance and propose a compensation method for the time-sampling effects. In digitization of analog STT autopilot, it is found that the stability margin of the fast dynamics is mostly affected to lead to rapid decrease. Under the this analysis, a composite digital controller with additional compensator for fast dynamics is proposed to improve the time-sampling effect and a simulation verifies the result.

• 한국기계가공학회지
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• 제14권3호
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• pp.85-91
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• 2015

The press-fit shaft is an important part used in automobiles, vessels, and trains. This study proposes an optimized design method to reduce damage that may occur in the press-fitted shaft by modifying the shape of the boss step of the press-fitted shaft. To reduce the time and cost of running the optimized design method, an approximate design optimization is applied and an optimized algorithm is generated using a genetic algorithm that is widely used in engineering fields and an approximate model using a response surface method. The planned experiments for the data that are needed to generate the approximate model use a central composite design (CCD) and Latin hypercube sampling (LHS), and the results of the approximate optimization using the above two design of experiments are to be compared.

• 응용통계연구
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• 제24권6호
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• pp.1115-1128
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• 2011

절사표본 설계는 관심변수의 분포가 오른쪽으로 치우쳐진 경우에 모집단 일부를 표본조사에서 제외시켜 조사의 효율을 높이는 방법이다. 그러나 전체 모집단의 총합 추정을 위해서는 버려진 절사 층에 관한 추론이 필요하게 된다. 기존에 사용하고 있는 많은 방법들은 절사층에서 표본조사를 하지 않고 알려진 보조정보와 조사자료를 이용하여 절사층 총합을 추정하며 이를 이용하여 전체 모집단의 총합을 추정한다. 본 논문에서는 절사층을 완전히 표본 층에서 제거하지 않고 조사의 편리성 및 효율성을 고려하여 최소의 표본을 추출한 후 모집단 전체 총합을 추정하는 방법을 제안하였다. 또한 모의실험을 통하여 제안된 추정법과 기존 방법의 우수성을 비교하였다.

• Journal of Mechanical Science and Technology
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• 제17권4호
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• pp.545-561
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• 2003

We use the first-passage-time formulation by Torquato, Kim and Cule ［J. Appl. Phys., Vol. 85, pp. 1560∼1571 (1999) ］, which makes use of the first-passage region in association with the diffusion tracer's Brownian movement, and develop a new efficient Brownian motion simulation method to compute the effective conductivity of digitized composite media. By using the new method, one can remarkably enhance the speed of the Brownian walkers sampling the medium and thus reduce the computation time. In the new method, we specifically choose the first-passage regions such that they coincide with two, four, or eight digitizing units according to the dimensionality of the composite medium and the local configurations around the Brownian walkers. We first obtain explicit solutions for the relevant first-passage-time equations in two-and three-dimensions. We then apply the new method to solve the illustrative benchmark problem of estimating the effective conductivities of the checkerboard-shaped composite media. for both periodic and random configurations. Simulation results show that the new method can reduce the computation time about by an order of magnitude.

• 응용통계연구
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• 제27권1호
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• pp.43-59
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• 2014

왜도가 심한 사업체 조사에서는 모집단의 일부를 제외하고 표본을 추출하는 방법인 절사표본추출법이 자주 사용된다. 절사층의 경우 표본 관리가 어렵고 조사비용이 많이 들기 때문에 이를 제외한 조사를 실시함으로써 조사의 효율을 높일 수 있다. 그러나 전체 모집단 추정을 위해서는 절사층의 정확한 총합 추정이 매우 중요하다. 최근 Hwang과 Shin (2013)은 Lavallee와 Hidiroglou (1988)가 제안한 LH 알고리즘을 이용하여 표본층을 층화한 후 표본층에서 얻어진 정보와 절사층에서 얻어진 정보를 결합한 복합추정량을 제안하였다. 본 논문에서는 비용함수를 고려한 새로운 표본 설계를 제안하고, 이를 위한 새로운 복합추정량을 제안하였다. 모의실험과 실제 자료 분석을 통하여 본 논문에서 제안한 복합추정량의 우수성을 확인하였다.