Powell inversion mechanical model of foundation parameters with generalized Bayesian theory

The inversion mechanical model of foundation parameters based on Powell optimizing theory was studied with generalized Bayesian theory. First, the generalized Bayesian objective function for foundation parameters was deduced with maximum likelihood theory. Then, the expectation expression and the covariance expression of the foundation parameters were obtained. After selecting the Winkler foundation as representative, the governing differential equations of the typical foundation were derived. With the orthogonal series transform method, the Fourier closed form solution of a moderately-thick plate on the Winkler foundation was achieved. After the optimal step length was determined with the quadratic parabolic interpolation method, the Powell inversion mechanical model of foundation parameters was resolved, and the corresponding inversion procedure was completed. Through particular example analysis, the highlight is that the Powell inversion mechanical model of foundation parameters with generalized Bayesian theory is correct and the derived Powell inversion model has universal significance, which can be applied in other kinds of foundation parameters. Besides, the Powell inversion iterative processes of foundation parameters have excellent numerical stability and convergence. The Powell optimizing theory is unconcerned with the partial derivatives of systematic responses to foundation parameters, which undoubtedly has a satisfying iterative efficiency compared with the available Kalman filtering or conjugate gradient inversion of the foundation parameters. The generalized Bayesian objective function can synchronously take the stochastic property of systematic parameters and systematic responses into account.     

Leak Detection in Water Distribution Systems Using Bayesian Theory and Fisher’s Law

A leak detection method based on Bayesian theory and Fisher’s law was developed for water distribution systems. A hydraulic model was associated with the parameters of leaks (location, extent). The randomness of parameter values was quantified by probability density function and updated by Bayesian theory. Values of the parameters were estimated based on Fisher’s law. The amount of leaks was estimated by back propagation neural network. Based on flow characteristics in water distribution systems, the location of leaks can be estimated. The effectiveness of the proposed method was illustrated by simulated leak data of node pressure head and flow rate of pipelines in a test pipe network, and the leaks were spotted accurately and renovated on time.     

基于贝叶斯证据框架下支持向量机建模的迭代优化控制

In the paper,an iterative method is presented to the optimal control of batch processes.Generally it is very difficult to acquire an accurate mechanistic model for a batch process.Because support vector machine is powerful for the problems characterized by small samples,nonlinearity,high dimension and local minima,support vector regression models are developed for the optimal control of batch processes where end-point properties are required.The model parameters are selected within the Bayesian evidence framework.Based on the model,an iterative method is used to exploit the repetitive nature of batch processes to determine the optimal operating policy.Numerical simulation shows that the iterative optimal control can improve the process performance through iterations.     

基于非仿射随机波动率模型的欧式认股权证的定价

利用快速傅里叶变换（FFT）方法推导出了标的资产服从非仿射随机波动率模型下的欧式认股权证定价公式。给出了非仿射随机波动率模型以及特征函数,应用傅里叶变换及其逆变换推导出了欧式认股权证的定价公式。     

Simulation of stochastic wind field for large complex structures based on modified Fourier spectrum

Simulation for stochastic wind field is very important in analyzing dynamic responses of large complex structures due to strong wind. The typical simulation method is the spectrum representation method (SRM), but the SRM has drawbacks of inferior precision in lower frequency and slow calculating speed. In view of this, the modified Fourier spectrum method (MFSM) is introduced into the simulation of stochastic wind field in this paper. In this method, phase information of wind velocity time history is determined by cross power spectral density (CPSD) between adjacent points, and the wind velocity time history with time and space correlation is generated by iterative modification for CPSD considering auto power spectral density (APSD). Simulation of the wind field for a long-span bridge is undertaken to verify the effectiveness of the MFSM. Simulation results of the SRM and the MFSM are compared. It can be concluded that the MFSM is more accurate and has higher calculation speed than the SRM.     

Stochastic simulation and analysis of geological corrosion defects in dam foundation

Uncertainty in geological structural modeling, especially geological corrosion(a kind of karst cave), is a bottleneck that restricts the development and application of geological computer modeling and effect estimation. To solve this issue, a stochastic modeling method based on the random field theory is proposed in comparison with the deterministic geometric modeling method. Then the constraint random field modeling method and the random field modeling method without constrained parameters are compared and analyzed. A case study shows that the novel stochastic simulation method is an effective tool to describe the distribution characteristics of corrosion parameters and reflect the updated geological prospecting information. The influence of geological corrosion on the dam behavior can also be better analyzed by using the stochastic simulation method. At the same time, the unconfined random field ignores the sample location information and may lead to higher variability. Therefore, the constraint random field modeling method can provide a useful reference for the numerical analysis under complex geological conditions.     

一类非线性动态模型的贝叶斯随机模拟

对一类非线性动态模型进行了随机模拟，利用Metropolis算法完成了样本的修正递推，并对模型进行各种预测和推断；然后利用观测误差构造统计量的方法实现了对模型的监控。     

不同图像之间拼接篡改的数字图像检测研究

对基于CFA（颜色滤波阵列）模型的篡改检测算法进行了改进。其检测过程为：首先,利用插值算法得到像素位置的预测误差,根据预测误差计算出CFA单元特征;然后,利用EM（期望最大化）算法估计特征模型的参数,算法对篡改位置的均值不做事先确定（从实验来看这种改进具有较好的效果）;最后,利用贝叶斯理论计算出每个像素点的似然率,根据似然率的不同来定位篡改区域。在进行单CFA阵列模式检测的情况下,对多种CFA阵列模式的图像也进行了检测分析,实验结果显示,该算法能够对多种CFA阵列模式的图像准确定位篡改区域。     

中国创业板市场收益率波动性的贝叶斯分析

采用随机波动（SV）模型,实证研究我国创业板市场收益率的波动性.通过基于Gibbs抽样的贝叶斯分析方法,较好地估计了模型参数.基于创业板市场数据的实证结果表明,带杠杆效应的SV-L模型相比基本的SV-N模型能更好地描述股票市场收益率的波动性.     

基于混沌模拟退火算法的BPNN模型的随机混沌系统辨识

文章针对随机混沌系统辨识引入贝叶斯正则化方法的BPNN模型,使神经网络具有自适应性和推广能力;并交替使用贝叶斯正则化算法和混沌退火算法对网络参数进行优化,使系统具有最佳参数．以Logistic系统为例进行仿真分析,结果表明辨识模型不仅能够拟合原混沌系统,而且训练后的网络对含噪声的随机混沌系统有很好的辨识能力,精度良好．为下一步的设计控制器对混沌系统进行控制消除混沌,奠定了良好的基础．     

混合效应随机微分方程的贝叶斯分析(英文)

采用带有随机微分方程的非线性混合效应模型对群体药物代谢动力学数据建模,通过在状态方程中引入随机项,将常微分方程扩展到随机微分方程.和常微分方程相比,随机微分方程可解决群体药物代谢动力学模型中相关残差问题.利用贝叶斯估计对非线性混合效应随机微分方程模型参数进行估计,给出群体参数及个体参数的精确后验分布,将Gibbs和Metropolis-Hastings算法相结合,给出参数估计值.通过计算机模拟和实例分析验证了方法的可靠性,结果表明利用非线性混合效应随机微分方程模型及贝叶斯估计方法分析群体药物代谢动力学数据是可行的.     

Seismic response analysis of damper-connected adjacent structures with stochastic parameters

Dynamic response analysis of damper connected adjacent multi-story structures with uncertain parameters is carried out. A formula of the multi degree of freedom （MDOF） for the structure-damper system with stochastic parameters is derived. The uncertainties of mass and stiffness are taken into consideration firstly. The ground acceleration is represented by Kanai-Tajimi filtered non-stationary process. The mean square random responses of structural displacement and story drift are chosen as the optimization objective. The variations of mean square responses of top floor displacements and bottom story drifts in neighboring structures with the damper stiffness and damping coefficient are analyzed in detail. Through the parametric study, the acquiring optimum parameters of damper are regarded as numerical results. Then, a reducing order model of the MDOF system for adjacent structures with mean parameters is presented. The explicit expressions for determining optimal parameters of Kelvin model-defined damper which is used to connect adjacent single degree of freedom （SDOF） structures subjected to a white-noise excitation are employed to achieve the appropriate damper parameters, which are called theory results. Through a comparative study, it can be found that the theory values of damper parameters are consistent with the results based on extensive parametric studies. The analytical results can be obtained by using the first natural frequencies and the total mass of the adjacent deterministic structures with mean parameters. The analytical formulas can be used to find appropriate parameters of damper between adjacent structures for engineering applications. The performance of damper is investigated on the basis of mitigations of mean square random responses of inter-story drifts, displacements and accelerations in adjacent structures. The numerical results demonstrate the robustness of coupled building control strategies.     

A Conditional Joint Modeling Approach for Locally Dependent Item Responses and Response Times

The assumption of conditional independence between the responses and the response times (RTs) for a given person is common in RT modeling. However, when the speed of a test taker is not constant, this assumption will be violated. In this article we propose a conditional joint model for item responses and RTs, which incorporates a covariance structure to explain the local dependency between speed and accuracy. To obtain information about the population of test takers, the new model was embedded in the hierarchical framework proposed by van der Linden ( 2007 ). A fully Bayesian approach using a straightforward Markov chain Monte Carlo (MCMC) sampler was developed to estimate all parameters in the model. The deviance information criterion (DIC) and the Bayes factor (BF) were employed to compare the goodness of fit between the models with two different parameter structures. The Bayesian residual analysis method was also employed to evaluate the fit of the RT model. Based on the simulations, we conclude that (1) the new model noticeably improves the parameter recovery for both the item parameters and the examinees’ latent traits when the assumptions of conditional independence between the item responses and the RTs are relaxed and (2) the proposed MCMC sampler adequately estimates the model parameters. The applicability of our approach is illustrated with an empirical example, and the model fit indices indicated a preference for the new model.     

论人力资本产权价值的计量基础及其模式

文章论述了将“税后纯收益”作为计量人力资本产权价值的基础,确定将随机报酬模型作为计量人力资本产权价值的主要计量模式,并对随机报酬模型进行了调整,使之更具有实际应用价值。     

随机波动率模型分析与应用

本文首先分析了金融时间序列中常用的随机波动率模型结构,介绍了马尔可夫链蒙特卡洛MCMC方法并采用基于MCMC模拟的贝叶斯分析对随机波动率模型的参数进行估计了,其次应用该模型对世界黄金价格指数时间序列的走势与波动进行分析,实证结果表明SV模型能较好的拟合金价走势并作出预测。     

随机固定资产投资系统数值解的收敛性

讨论了含有非局部和时滞边界条件的分布参数随机固定资产投资系统模型的数值解,用Euler方法给出系统的逼近序列,利用随机分析中的It(?)公式,Burkholder-Davis-Gundy不等式和Cauchy-Schwarz不等式,在局部Lipschitz条件下,证明了随机固定资产投资系统数值解的有界性和收敛性.     

汽车零部件循环取货SCC选址研究—-以远距离零部件供应商为例

针对国内远距离汽车零部件供应商循环取货理论和应用缺乏系统研究的现状,在总结汽车零部件循环取货运作模式的基础上,以远距离汽车零部件供应商循环取货SCC为出发点,采用改进的欧几里德模型,运用迭代计算的基础上综合考虑各种定性、定量因素对SCC的选址问题进行实证研究,为远距离汽车零部件供应商循环取货理论和应用的系统研究打下了一定的基础。     

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model

Bock, Muraki, and Pfeiffenberger (1988) proposed a dichotomous item response theory (IRT) model for the detection of differential item functioning (DIF), and they estimated the IRT parameters and the means and standard deviations of the multiple latent trait distributions. This IRT DIF detection method is extended to the partial credit model (Masters, 1982; Muraki, 1993) and presented as one of the multiple-group IRT models. Uniform and non-uniform DIF items and heterogeneous latent trait distributions were used to generate polytomous responses of multiple groups. The DIF method was applied to this simulated data using a stepwise procedure. The standardized DIF measures for slope and item location parameters successfully detected the non-uniform and uniform DIF items as well as recovered the means and standard deviations of the latent trait distributions.This stepwise DIF analysis based on the multiple-group partial credit model was then applied to the National Assessment of Educational Progress (NAEP) writing trend data.     

平面图案教学体系的再认识

针对高校图案课的系统性我们提出了一个平面图案概念，并系统地将传统纹样与构成理论结合起来，指出两大理论之间分与合的关系，提出了动态线的造型，节奏与韵律相结合，从而使高校设计专业造型基础课系统化，理性化。     

贝叶斯决策理论与归纳逻辑

贝叶斯决策理论是主观贝叶斯派归纳理论的重要组成部分。现代归纳逻辑遇到 “归纳接受”的难题,一部分学者用贝叶斯决策理论的思想和方法解决这个问题,后来导致了信念 修正理论的产生。从只考察归纳推理前提与结论之间的逻辑联系到全面地刻画归纳推理的动态 认知过程,现代归纳理论的发展呈现出一种新的面貌,而贝叶斯决策理论是其中承上启下的一 环。对贝叶斯决策理论的检验和修正导致了富有成果的新理论的建立。