• Title/Summary/Keyword: most probable state

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An Algorithm For Approximating The Reliability of Network with Multistate Units (다중상태 유닛들의 망 신뢰도 근사 계산을 위한 알고리즘)

  • 오대호;염준근
    • Journal of Korean Society for Quality Management
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    • v.30 no.1
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    • pp.162-171
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    • 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.

An Algorithm For Approximating The Performance of Multi-mode Network System Using Algebraic Property of System States (시스템 상태의 대수적 성질을 이용한 다중모드 네트워크 시스템 성능 근사계산 알고리즘)

  • Oh, Dae-Ho
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.12
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    • pp.127-137
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    • 2009
  • A practical algorithm of generating most probable states in decreasing order of probability of the network system state is suggested for approximating the performance of multi-mode network system using algebraic structure of the system states. Most complex system having network structure with multi-mode unit state is difficult to evaluate the performance or reliability due to exponentially increasing size of state space. Hence not an exact computing method but an approximated one is reasonable approach to solve the problem. To achieve the goal we should enumerate the network system states in order as a pre-processing step. In this paper, we suggest an improved algorithm of generating most probable multi-mode states to get the ordered system states efficiently. The method is compared with the previous algorithms in respective to memory requirement and empirical computing time. From the experiment proposed method has some advantages with regard to the criterion of algorithm performance. We investigate the advantages and disadvantage by illustrating experiment examples.

Reliability Analysis for Composite Laminated Plate Using Hybrid Response Surface Method (복합 반응면 기법을 이용한 복합재 적층판의 신뢰성해석)

  • Lee, Seok-Je;Kim, In-Gul
    • Composites Research
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    • v.23 no.2
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    • pp.40-47
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    • 2010
  • In this paper, the hybrid response surface method(HRSM) is proposed and examined. Hybrid response surface method calculate a approximate model repeatedly based on MPP coordinates. To verify the performance, probability of failure, MPP(Most Probable failure Point) and reliability index are calculated for nonlinear function and composite laminated plate by using reliability analysis method and compared with results by using typical response surface method(RSM). Probability of failure is calculated under the assumption of the nonlinear limit state equation and given failure criterion. The results of proposed method shows performance improvement in estimating the probability of failure.

Decomposable polynomial response surface method and its adaptive order revision around most probable point

  • Zhang, Wentong;Xiao, Yiqing
    • Structural Engineering and Mechanics
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    • v.76 no.6
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    • pp.675-685
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    • 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.

Optimizaiton of PSS Parametes and Identification of Optimum Site for PSS Applications (PSS 파라미터 최적화 및 최적위치선정에 관한 연구)

  • 박영문;정정원
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.40 no.5
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    • pp.453-459
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    • 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.

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The hybrid uncertain neural network method for mechanical reliability analysis

  • Peng, Wensheng;Zhang, Jianguo;You, Lingfei
    • International Journal of Aeronautical and Space Sciences
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    • v.16 no.4
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    • pp.510-519
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    • 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.

Comparison between Parametric and Semi-parametric Cox Models in Modeling Transition Rates of a Multi-state Model: Application in Patients with Gastric Cancer Undergoing Surgery at the Iran Cancer Institute

  • Zare, Ali;Mahmoodi, Mahmood;Mohammad, Kazem;Zeraati, Hojjat;Hosseini, Mostafa;Naieni, Kourosh Holakouie
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.11
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    • pp.6751-6755
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    • 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.

ReliabIlity analysis of containment building subjected to earthquake load using response surface method

  • Lee, Seong Lo
    • Computers and Concrete
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    • v.3 no.1
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    • pp.1-15
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    • 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.

The ralationship between apex seal breakage and engine detonation in a wankel engine (Wankel 엔진의 에이펙스 시일 파손과 엔진 이상폭발과의 관계)

  • 김승수
    • Journal of the korean Society of Automotive Engineers
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    • v.7 no.1
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    • pp.48-54
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    • 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.

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Contextual Modeling and Generation of Texture Observed in Single and Multi-channel Images

  • Jung, Myung-Hee
    • Korean Journal of Remote Sensing
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    • v.17 no.4
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    • pp.335-344
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    • 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.