• 품질경영학회지
• /
• 제30권1호
• /
• pp.162-171
• /
• 2002

A practical algorithm of generating most probable states in decreasing order of probability, given the probability of each unit\`s state, is suggested for approximating reliability(performability) evaluation of a network with multistate(multimode) units. Method of approximating network reliability for a given measure with most probable states is illustrated with a numerical example. The proposed method in this paper is compared with the previous method regarding memory requirement. Our method has some advantages for computation and achieves improvement with regard to memory requirement for a certain condition judging from the computation experiment.

• 한국컴퓨터정보학회논문지
• /
• 제14권12호
• /
• pp.127-137
• /
• 2009

본 논문에서는 다중모드를 갖는 장치 구성요소들의 네트워크 구조를 갖는 시스템 혹은 통신 네트워크에서 성능 품질 혹은 신뢰도 근사계산을 위해서 네트워크 시스템 상태들의 확률크기에 관해 최고 가능 상태들만을 생성하는 알고리즘을 제안한다. 대부분의 네트워크 시스템 같은 복잡한 시스템들은 장치들의 수나 장치들의 다중 모드의 수가 증가함에 따른 기하급수적 상태 공간의 증가로 인해 그 성능이나 신뢰도를 직접 계산하는 것이 매우 어려운 경우가 많다. 따라서 근사계산의 해법이 더욱 타당한 접근법이라 할 수 있다. 이때, 시스템의 기대 성능이나 신뢰도 계산을 위해서는 시스템 상태와 그 상태 확률을 통해 기댓값을 산출하여야 한다. 이때, 근사계산을 통한 접근 방법에서 사전에 수행되어야 하는 것은 네트워크 시스템 상태들의 발생 가능 순서로 나열해야 하는 것이 필요하다. 이에 본 논문에서는 시스템 상태들 중 가장 발생 가능성이 큰 상태들을 찾고 이로부터 네트워크 성능이나 신뢰도의 근사 값을 구하는데 활용할 수 있는 방법을 제안한다. 제안된 알고리즘은 기존의 방법과 자원의 효율성 측면 중에서 메모리 효율성을 고려하여 실험을 통해 예시하고 장 단점을 논의하고자 한다.

• Composites Research
• /
• 제23권2호
• /
• pp.40-47
• /
• 2010

본 논문에서는 복합 반응면 기법을 제안하고 성능을 고찰하였다. 복합 반응면 기법은 MPP의 좌표를 기준으로 하여 근사모델을 반복 계산하는 기법이다. 성능을 검증하기 위해 비선형 함수와 복합재 적층판에 대하여 신뢰성 해석 기법을 적용하여 파괴확률, MPP(Most Probable failure Point), 신뢰도 지수를 계산하고 일반적인 반응면 기법의 결과와 비교하였다. 파괴확률은 비선형 한계상태식을 가정하고 임의의 파괴 기준을 정의하여 계산하였다. 제안한 복합 반응면 기법을 이용하여 파괴확률을 계산한 결과 일반적인 반응면 기법보다 향상된 성능을 나타내었다.

• Structural Engineering and Mechanics
• /
• 제76권6호
• /
• pp.675-685
• /
• 2020

As the classical response surface method (RSM), the polynomial RSM is so easy-to-apply that it is widely used in reliability analysis. However, the trade-off of accuracy and efficiency is still a challenge and the "curse of dimension" usually confines RSM to low dimension systems. In this paper, based on the univariate decomposition, the polynomial RSM is executed in a new mode, called as DPRSM. The general form of DPRSM is given and its implementation is designed referring to the classical RSM firstly. Then, in order to balance the accuracy and efficiency of DPRSM, its adaptive order revision around the most probable point (MPP) is proposed by introducing the univariate polynomial order analysis, noted as RDPRSM, which can analyze the exact nonlinearity of the limit state surface in the region around MPP. For testing the proposed techniques, several numerical examples are studied in detail, and the results indicate that DPRSM with low order can obtain similar results to the classical RSM, DPRSM with high order can obtain more precision with a large efficiency loss; RDPRSM can perform a good balance between accuracy and efficiency and preserve the good robustness property meanwhile, especially for those problems with high nonlinearity and complex problems; the proposed methods can also give a good performance in the high-dimensional cases.

• 대한전기학회논문지
• /
• 제40권5호
• /
• pp.453-459
• /
• 1991

This paper presents a new algorithm to select optimal parameters and location of power system stabilizer (PSS). A new performance measure, which evaluates the share of a particular mode among state responses, is introduced. The gradient of the performance measure with respect to PSS parametes is derived in an explicit form, so optimal parameters of PSS can be obtained by the steepest descent method. The machine, with which it is most probable to reduce the performance measure, is identified as the optimum site for PSS application.

• International Journal of Aeronautical and Space Sciences
• /
• 제16권4호
• /
• pp.510-519
• /
• 2015

Concerning the issue of high-dimensions, hybrid uncertainties of randomness and intervals including implicit and highly nonlinear limit state function, reliability analysis based on the hybrid uncertainty reliability mode combining with back propagation neural network (HU-BP neural network) is proposed in this paper. Random variables and interval variables are as input layer of the neural network, after the training and approximation of the neural network, the response variables are obtained through the output layer. Reliability index is calculated by solving the optimization model of the most probable point (MPP) searching in the limit state band. Two numerical cases are used to demonstrate the method proposed in this paper, and finally the method is employed to solving an engineering problem of the aerospace friction plate. For this high nonlinear, small failure probability problem with interval variables, this method could achieve a good analysis result.

• Asian Pacific Journal of Cancer Prevention
• /
• 제14권11호
• /
• pp.6751-6755
• /
• 2013

Background: Research on cancers with a high rate of mortality such as those occurring in the stomach requires using models which can provide a closer examination of disease processes and provide researchers with more accurate data. Various models have been designed based on this issue and the present study aimed at evaluating such models. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at Iran Cancer Institute from 1995 to 1999 were analyzed. Cox-Snell Residuals and Akaike Information Criterion were used to compare parametric and semi-parametric Cox models in modeling transition rates among different states of a multi-state model. R 2.15.1 software was used for all data analyses. Results: Analysis of Cox-Snell Residuals and Akaike Information Criterion for all probable transitions among different states revealed that parametric models represented a better fitness. Log-logistic, Gompertz and Log-normal models were good choices for modeling transition rate for relapse hazard (state $1{\rightarrow}state$ 2), death hazard without a relapse (state $1{\rightarrow}state$ 3) and death hazard with a relapse (state $2{\rightarrow}state$ 3), respectively. Conclusions: Although the semi-parametric Cox model is often used by most cancer researchers in modeling transition rates of multistate models, parametric models in similar situations- as they do not need proportional hazards assumption and consider a specific statistical distribution for time to occurrence of next state in case this assumption is not made - are more credible alternatives.

• Computers and Concrete
• /
• 제3권1호
• /
• pp.1-15
• /
• 2006

The seismic safety of reinforced concrete containment building can be evaluated by probabilistic analysis considering randomness of earthquake, which is more rational than deterministic analysis. In the safety assessment of earthquake-resistant structures by the deterministic theory, it is not easy to consider the effects of random variables but the reliability theory and random vibration theory are useful to assess the seismic safety with considering random effects. The reliability assessment of reinforced concrete containment building subjected to earthquake load includes the structural analysis considering random variables such as load, resistance and analysis method, the definition of limit states and the reliability analysis. The reliability analysis procedure requires much time and labor and also needs to get the high confidence in results. In this study, random vibration analysis of containment building is performed with random variables as earthquake load, concrete compressive strength, modal damping ratio. The seismic responses of critical elements of structure are approximated at the most probable failure point by the response surface method. The response surface method helps to figure out the quantitative characteristics of structural response variability. And the limit state is defined as the failure surface of concrete under multi-axial stress, finally the limit state probability of failure can be obtained simply by first-order second moment method. The reliability analysis for the multiaxial strength limit state and the uniaxial strength limit state is performed and the results are compared with each other. This study concludes that the multiaxial failure criterion is a likely limit state to predict concrete failure strength under combined state of stresses and the reliability analysis results are compatible with the fact that the maximum compressive strength of concrete under biaxial compression state increases.

• 오토저널
• /
• 제7권1호
• /
• pp.48-54
• /
• 1985

One of the most probable reason of the apex seal damage in IR-2500 industrial Wankel (rotary) engine was believed to be the engine detonation. Both analytical and experimental studies were made with a view th find out engine detonation pressure. The stagnation detonation pressure $p_{03}$' was estimated based on the data from IR-2500 engine detonation tests, such as engine firing pressure, state of fresh charge at BDC and polytropic compression exponent. The estimated stagnation detonation pressure for the natural gas fueled IR-2500 engine was in excess of 3,700 psia. With natural gas liquid added to the natural gas the octane value of the fuel was lowered, thus, making the engine more prone to detonate. The estimated detonation pressure for the case with the mixed fuel was about 3,400 psia which was sufficiently high to break the apex seal. The subsequent engine lab tests performed on two identical engines with sole difference in the apex seal thickness between the two engines proved that the engine knock, in fact, was the villain of the apex seal failure.ilure.

• 대한원격탐사학회지
• /
• 제17권4호
• /
• pp.335-344
• /
• 2001

Texture is extensively studied in a variety of image processing applications such as image segmentation and classification because it is an important property to perceive regions and surfaces. This paper focused on the analysis and synthesis of textured single and multiband images using Markov Random Field model considering the existent spatial correlation. Especially, for multiband images, the cross-channel correlation existing between bands as well as the spatial correlation within band should be considered in the model. Although a local interaction is assumed between the specified neighboring pixels in MRF models, during the maximization process, short-term correlations among neighboring pixels develop into long-term correlations. This result in exhibiting phase transition. In this research, the role of temperature to obtain the most probable state during the sampling procedure in discrete Markov Random Fields and the stopping rule were also studied.