• 청정기술
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• 제7권2호
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• pp.119-126
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• 2001

인공신경 회로망과 통계적 방법을 이용하여 오존 형성의 예측에 관한 연구를 수행하였다. 파라미터 평가방법으로는 실시간 파라미터를 평가하기 위하여 ELS 및 RML 방법이 사용되었으며 오존 형성의 모델로는 ARMAX 모델을 사용하였다. 또한 3층 구조를 갖는 인공신경 회로망 방법을 이용하여 오존 형성의 예측 시험을 수행하였으며 본 연구에 사용된 통계적 방법의 성능을 평가하기 위하여 오존 형성의 예측결과를 실제 자료와 비교 분석을 하였다. 실제 자료와의 비교를 통하여 파라미터 평가 방법 및 인공신경 회로망 방법에 근거한 예측방법이 제한된 예측 구간 내에서 만족할 만한 성능을 보임을 확인할 수 있었다.

• 품질경영학회지
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• 제35권4호
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• pp.61-66
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• 2007

The performance of a building material degrades as time goes by and the failure of the material is often defined as the point at which the performance of the material reaches a pre-specified degraded level. Based on a stochastic deterioration model, a performance based service life prediction method for building materials and components is developed. As a stochastic degradation model, a gamma process is considered and lifetime distribution and service life of a material are predicted using the degradation model. A numerical example is provided to illustrate the use of the proposed service life prediction method.

• 한국지진공학회논문집
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• 제5권4호
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• pp.17-26
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• 2001

한반도 남부에서 발생 가능한 강지진동의 최대 지반운동과 주파수에 따른 특성을 추계학적 모사법을 이용하여 간접적으로 추정하였다. 또한 추계학적 모사법에 적용할 진원과 지진파 감쇠에 관한 입력자료를 계산하였다. 응력강하($\Delta$$\sigma$)는 한반도 남부와 미국 동부 및 중국의 연구결과를 종합하여 100-bar로 추정하였다. 감쇠상수는 x는 1996년 9월부터 1997년 12월까지 발생한 지진 중 비교적 기록상태가 양호한 57개의 관측자료를 이용하여 계산하였으며 진원거리(R)에 대하여 0.00112+0.000224 R로 추정되었다. 이와 같은 응력강하($\Delta$$\sigma$)와 감쇠상수 x등의 입력자료를 추계학적 모사법에 적용한 결과를 바탕으로 진원거리에 따른 강진동 감쇠공식을 유도하였다.한 결과를 바탕으로 진원거리에 따른 강진동 감쇠공식을 유도하였다.

• Journal of Electrical Engineering and Technology
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• 제12권3호
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• pp.1053-1063
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• 2017

Power prediction is critical to improve power efficiency in Smart Grids. Markov chain provides a useful tool for power prediction. With careful investigation of practical power datasets, we find an interesting phenomenon that the stochastic property of practical power datasets does not follow the Markov features. This mismatch affects the prediction accuracy if directly using Markov prediction methods. In this paper, we innovatively propose a spatial transform based data processing to alleviate this inconsistency. Furthermore, we propose an enhanced power prediction method, named by Spatial Mapping Markov-Difference (SMMD), to guarantee the prediction accuracy. In particular, SMMD adopts a second prediction adjustment based on the differential data to reduce the stochastic error. Experimental results validate that the proposed SMMD achieves an improvement in terms of the prediction accuracy with respect to state-of-the-art solutions.

• 한국터널지하공간학회 논문집
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• 제12권3호
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• pp.265-274
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• 2010

터널에서 암반구조의 복잡성으로 인해 사전에 예측 할 수 없었던 암반의 붕락이 발생하여, 붕락대책에 막대한 비용과 시간을 낭비하는 사례가 많다. 암반 불연속면의 복잡성을 사전 조사 단계에서 충분히 파악하거나 대책을 수립하는 것은 어렵다. 최근 터널의 정보화 설계시공이 중요시 되어지고 있다. 본 연구에서는 터널의 굴착 전에 관찰된 정보를 최대한 활용하여 불안정한 암반블럭을 사전에 예측하기 위하여 신 하이브리드 추계학적-확정론적 암반블럭 해석기법을 제안하고, 현지에서 관찰한 불연속면 정보를 근거로 하여 터널현장에 적용했다. 터널현장에서의 해석결과를 비교 검토하여, 터널의 신 하이브리드 추계학적-확정론적 암반블럭 해석기법의 타당성과 적용성에 대한 검증을 하였다.

• 대한수학회지
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• 제38권3호
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• pp.657-667
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• 2001

We propose a statistical interpolation approximate solution for a nonlinear stochastic integral equation of a stock price process. The proposed method has the order O(h$^2$) of local error under the weaker conditions of $\mu$ and $\sigma$ than those of Milstein' scheme.

• 한국신뢰성학회:학술대회논문집
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• 한국신뢰성학회 2000년도 춘계학술대회 발표논문집
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• pp.213-222
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• 2000

In present study, a stochastic model is developed for the low cycle fatigue life prediction and reliability assessment of 316L stainless steel under variable multiaxial loading. In the proposed model, fatigue phenomenon is considered as a Markov process, and damage vector and reliability are defined on every plane. Any low cycle fatigue damage evaluating method can be included in the proposed model. The model enables calculation of statistical reliability and crack initiation direction under variable multiaxial loading, which are generally not available. In present study, a critical plane method proposed by Kandil et al., maximum tensile strain range, and von Mises equivalent strain range are used to calculate fatigue damage. When the critical plane method is chosen, the effect of multiple critical planes is also included in the proposed model. Maximum tensile strain and von Mises strain methods are used for the demonstration of the generality of the proposed model. The material properties and the stochastic model parameters are obtained from uniaxial tests only. The stochastic model made of the parameters obtained from the uniaxial tests is applied to the life prediction and reliability assessment of 316L stainless steel under variable multiaxial loading. The predicted results show good accordance with experimental results.

• Structural Engineering and Mechanics
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• 제55권3호
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• pp.525-534
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• 2015

A new structural dynamic fuzzy reliability analysis under stochastic loads which are applied several times is proposed in this paper. The fuzzy reliability prediction models based on time responses with and without strength degeneration are established using the stress-strength interference theory. The random loads are applied several times and fuzzy structural strength is analyzed. The efficiency of the proposed method is demonstrated numerically through an example. The results have shown that the proposed method is practicable, feasible and gives a reasonably accurate prediction. The analysis shows that the probabilistic reliability is a special case of fuzzy reliability and fuzzy reliability of structural strength without degeneration is also a special case of fuzzy reliability with structural strength degeneration.

• 한국건설관리학회논문집
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• 제6권1호
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• pp.73-79
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• 2005

This paper, introduces a Stochastic Project Scheduling Simulation system (SPSS III) developed by the author to predict a project completion probability in a certain time. The system integrates deterministic CPM, probabilistic PERT, and stochastic Discrete Event Simulation (DES) scheduling methods into one system. It implements automated statistical analysis methods for computing the minimum number of simulation runs, the significance of the difference between independent simulations, and the confidence interval for the mean project duration as well as sensitivity analysis method in What-if analyzer component. The SPSS 111 gives the several benefits to researchers in that it (1) complements PERT and Monte Carlo simulation by using stochastic activity durations via a web based JAVA simulation over the Internet, (2) provides a way to model a project network having different probability distribution functions, (3) implements statistical analyses method which enable to produce a reliable prediction of the probability of completing a project in a specified time, and (4) allows researchers to compare the outcome of CPM, PERT and DES under different variability or skewness in the activity duration data.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.1851-1856
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• 2003

A new Lagrangian stochastic dispersion model is developed by combining the GLM(generalized Langevin model) and the elliptic relaxation method. Under the physically plausible assumptions a simple analytical solution of elliptic relaxation is obtained. To compare the performance of our model with other model, the statistics of particle velocity as well as concentration are investigated. Numerical simulation results show good agreement with available experimental data.