• Title/Summary/Keyword: stochastic characteristic

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Stochastic analysis for uncertain deformation of foundations in permafrost regions

  • Wang, Tao;Zhou, Guoqing;Wang, Jianzhou;Zhao, Xiaodong;Yin, Leijian
    • Geomechanics and Engineering
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    • v.14 no.6
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    • pp.589-600
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    • 2018
  • For foundations in permafrost regions, the displacement characteristics are uncertain because of the randomness of temperature characteristics and mechanical parameters, which make the structural system have an unexpected deviation and unpredictability. It will affect the safety of design and construction. In this paper, we consider the randomness of temperature characteristics and mechanical parameters. A stochastic analysis model for the uncertain displacement characteristic of foundations is presented, and the stochastic coupling program is compiled by Matrix Laboratory (MATLAB) software. The stochastic displacement fields of an embankment in a permafrost region are obtained and analyzed by Neumann stochastic finite element method (NSFEM). The results provide a new way to predict the deformation characteristics of foundations in permafrost regions, and it shows that the stochastic temperature has a different influence on the stochastic lateral displacement and vertical displacement. Construction disturbance and climate warming lead to three different stages for the mean settlement of characteristic points. For the stochastic settlement characteristic, the standard deviation increases with time, which imply that the results of conventional deterministic analysis may be far from the true value. These results can improve our understanding of the stochastic deformation fields of embankments and provide a theoretical basis for engineering reliability analysis and design in permafrost regions.

Bayesian hierarchical model for the estimation of proper receiver operating characteristic curves using stochastic ordering

  • Jang, Eun Jin;Kim, Dal Ho
    • Communications for Statistical Applications and Methods
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    • v.26 no.2
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    • pp.205-216
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    • 2019
  • Diagnostic tests in medical fields detect or diagnose a disease with results measured by continuous or discrete ordinal data. The performance of a diagnostic test is summarized using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The diagnostic test is considered clinically useful if the outcomes in actually-positive cases are higher than actually-negative cases and the ROC curve is concave. In this study, we apply the stochastic ordering method in a Bayesian hierarchical model to estimate the proper ROC curve and AUC when the diagnostic test results are measured in discrete ordinal data. We compare the conventional binormal model and binormal model under stochastic ordering. The simulation results and real data analysis for breast cancer indicate that the binormal model under stochastic ordering can be used to estimate the proper ROC curve with a small bias even though the sample sizes were small or the sample size of actually-negative cases varied from actually-positive cases. Therefore, it is appropriate to consider the binormal model under stochastic ordering in the presence of large differences for a sample size between actually-negative and actually-positive groups.

General Properties of Quantization Systems with a Stochastic Reference (Stochastic reference를 가진 량자화 시스템의 일반적인 성질)

  • 한선신
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.18 no.2
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    • pp.44-53
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    • 1981
  • This paper deals with two quantization systems with a stochastic refernce and gives the unified statical properties of the two systems. The conditions are derived for the invariance of the output quantized signal with respect to the imput signal for the two systems and it is shown that they are same. The correlation function by a polarity method using stochastic reference signals is show to be a special case of the general properties derived here. We have also shown that the classical stochastic computing is derived from the general properties of the first system and that L.G. roberts has used a special characteristic of the general properties of the second system in his image processing.

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THE LAW OF A STOCHASTIC INTEGRAL WITH TWO INDEPENDENT BIFRACTIONAL BROWNIAN MOTIONS

  • Liu, Junfeng
    • Communications of the Korean Mathematical Society
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    • v.26 no.4
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    • pp.669-684
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    • 2011
  • In this note, we obtain the expression of the characteristic fucntion of the random variable $\int_o^TB_s^{{\alpha},{\beta}}dB_s^{H,K}$, where $B^{{\alpha},{\beta}}$ and $B^{H,K}$ are two independent bifractional Brownian motions with indices ${\alpha}{\in}(0,1),{\beta}{\in}(0, 1]$ and $HK{\in}(\frac{1}{2},\;1)$ respectively.

Vibration and stability of fluid conveying pipes with stochastic parameters

  • Ganesan, R.;Ramu, S. Anantha
    • Structural Engineering and Mechanics
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    • v.3 no.4
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    • pp.313-324
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    • 1995
  • Flexible cantilever pipes conveying fluids with high velocity are analysed for their dynamic response and stability behaviour. The Young's modulus and mass per unit length of the pipe material have a stochastic distribution. The stochastic fields, that model the fluctuations of Young's modulus and mass density are characterized through their respective means, variances and autocorrelation functions or their equivalent power spectral density functions. The stochastic non self-adjoint partial differential equation is solved for the moments of characteristic values, by treating the point fluctuations to be stochastic perturbations. The second-order statistics of vibration frequencies and mode shapes are obtained. The critical flow velocity is first evaluated using the averaged eigenvalue equation. Through the eigenvalue equation, the statistics of vibration frequencies are transformed to yield critical flow velocity statistics. Expressions for the bounds of eigenvalues are obtained, which in turn yield the corresponding bounds for critical flow velocities.

OPTION PRICING UNDER STOCHASTIC VOLATILITY MODEL WITH JUMPS IN BOTH THE STOCK PRICE AND THE VARIANCE PROCESSES

  • Kim, Ju Hong
    • The Pure and Applied Mathematics
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    • v.21 no.4
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    • pp.295-305
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    • 2014
  • Yan & Hanson [8] and Makate & Sattayatham [6] extended Bates' model to the stochastic volatility model with jumps in both the stock price and the variance processes. As the solution processes of finding the characteristic function, they sought such a function f satisfying $$f({\ell},{\nu},t;k,T)=exp\;(g({\tau})+{\nu}h({\tau})+ix{\ell})$$. We add the term of order ${\nu}^{1/2}$ to the exponent in the above equation and seek the explicit solution of f.

Optimum Design of the Brushless Motor Considering Parameter Tolerance (설계변수 공차를 고려한 브러시리스 모터 출력밀도 최적설계)

  • Son, Byoung-Ook;Lee, Ju
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.59 no.9
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    • pp.1600-1604
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    • 2010
  • This paper presents the optimum design of the brushless motor to maximize the output power per weight considering the design parameter tolerance. The optimization is proceeded by commercial software that is adopted the scatter-search algorithm and the characteristic analysis is conducted by FEM. The stochastic optimum design results are compared with those of the deterministic optimization method. We can verify that the results of the stochastic optimization is superior than that of deterministic optimization.

Stochastic analysis of external and parametric dynamical systems under sub-Gaussian Levy white-noise

  • Di Paola, Mario;Pirrotta, Antonina;Zingales, Massimiliano
    • Structural Engineering and Mechanics
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    • v.28 no.4
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    • pp.373-386
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    • 2008
  • In this study stochastic analysis of non-linear dynamical systems under ${\alpha}$-stable, multiplicative white noise has been conducted. The analysis has dealt with a special class of ${\alpha}$-stable stochastic processes namely sub-Gaussian white noises. In this setting the governing equation either of the probability density function or of the characteristic function of the dynamical response may be obtained considering the dynamical system forced by a Gaussian white noise with an uncertain factor with ${\alpha}/2$- stable distribution. This consideration yields the probability density function or the characteristic function of the response by means of a simple integral involving the probability density function of the system under Gaussian white noise and the probability density function of the ${\alpha}/2$-stable random parameter. Some numerical applications have been reported assessing the reliability of the proposed formulation. Moreover a proper way to perform digital simulation of the sub-Gaussian ${\alpha}$-stable random process preventing dynamical systems from numerical overflows has been reported and discussed in detail.

THE VALUATION OF VARIANCE SWAPS UNDER STOCHASTIC VOLATILITY, STOCHASTIC INTEREST RATE AND FULL CORRELATION STRUCTURE

  • Cao, Jiling;Roslan, Teh Raihana Nazirah;Zhang, Wenjun
    • Journal of the Korean Mathematical Society
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    • v.57 no.5
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    • pp.1167-1186
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    • 2020
  • This paper considers the case of pricing discretely-sampled variance swaps under the class of equity-interest rate hybridization. Our modeling framework consists of the equity which follows the dynamics of the Heston stochastic volatility model, and the stochastic interest rate is driven by the Cox-Ingersoll-Ross (CIR) process with full correlation structure imposed among the state variables. This full correlation structure possesses the limitation to have fully analytical pricing formula for hybrid models of variance swaps, due to the non-affinity property embedded in the model itself. We address this issue by obtaining an efficient semi-closed form pricing formula of variance swaps for an approximation of the hybrid model via the derivation of characteristic functions. Subsequently, we implement numerical experiments to evaluate the accuracy of our pricing formula. Our findings confirm that the impact of the correlation between the underlying and the interest rate is significant for pricing discretely-sampled variance swaps.

Stochastic Mobility Model Design in Mobile WSN (WSN 노드 이동 환경에서 stochastic 모델 설계)

  • Yun, Dai Yeol;Yoon, Chang-Pyo;Hwang, Chi-Gon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.8
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    • pp.1082-1087
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    • 2021
  • In MANET(mobile ad hoc network), Mobility models vary according to the application-specific goals. The most widely used Random WayPoint Mobility Model(RWPMM) is advantageous because it is simple and easy to implement, but the random characteristic of nodes' movement is not enough to express the mobile characteristics of the entire sensor nodes' movements. The random mobility model is insufficient to express the inherent movement characteristics of the entire sensor nodes' movements. In the proposed Stochastic mobility model, To express the overall nodes movement characteristics of the network, the moving nodes are treated as random variables having a specific probability distribution characteristic. The proposed Stochastic mobility model is more stable and energy-efficient than the existing random mobility model applies to the routing protocol to ensure improved performances in terms of energy efficiency.