一类单边截断型分布族参数的经验Bayes检验

讨论一类单边截断型分布族位置参数的经验Ｂａｙｅｓ检验问题，文中构造了经验Ｂａｙｅｓ判决函数，证明了它具有渐近最优的性质，并且获得了收敛速度。     

基于条件生成式对抗网络的油藏单井产量预测模型

为克服机器学习方法在油藏单井产量预测中的过拟合问题,提高油田生产中的产量预测精度,提出一种基于条件生成式对抗网络(CGAN)的油藏单井产量预测模型。该模型使用长短期记忆、全连接等基础神经网络,构建生成和判别网络模型。生成网络模型以产量影响因素为条件输入,生成预测产量数据,利用对数损失函数评价预测数据与真实数据之间的偏差,通过条件生成式对抗网络的博弈训练,并结合贝叶斯超参数优化算法,优化模型结构,综合提高模型的泛化能力。基于Eclipse数值模拟软件建立同一井网条件下不同地质和生产条件下的油藏单井产量数据库,以地质与生产条件等产量影响因素作为模型的条件输入,进行油藏单井产量预测。结果表明：与全连接神经网络(FCNN)、随机森林(RF)以及长短期记忆神经网络(LSTM)模型的预测结果相比,CGAN模型在测试集上的平均绝对百分比误差分别提升了2.59%、 0.81%以及1.72%,并且过拟合比最小(1.027)。说明CGAN降低了机器学习产量预测模型的过拟合程度,提高了模型的泛化能力与预测精度,验证了所提算法的优越性,对指导油田高效开发和保障我国能源战略安全具有重要意义。     

Four-component superlattice empirical pseudopotential method for InAs/GaSb superlattices

For the design of InAs/GaSb superlattice (SL) heterojunction infrared photodetectors with very low dark current we have extended the standard two-component superlattice empirical pseudopotential method (SEPM) and implemented a four-component model including interface layers. For both models, the calculated bandgap values for a set of SL samples are compared to bandgaps determined by photoluminescence measurements. While the bandgap resulting from the two-component model agrees well with experimental data for SL structures with individual layer thicknesses of 7 monolayers and more, we show that for SLs with thinner GaSb layers the four-component SEPM model is accurate, when the As-content in the interface and barrier layers is included in the model.     

Nonsmooth analysis of vector-valued mappings with contributions to nondifferentiable programming

We define order Lipschitz mappings from a Banach space to an order complete vector lattice and present a nonsmooth analysis for such functions. In particular, we establish properties of a generalized directional derivative and gradient and derive results concerning a calculus of generalized gradients (i.e., calculation of the generalized gradient of f when f = f₁ + f₂, f = f · ₂, etc.). We show the relevance of the above analysis to nondifferentiaile programming by deriving optimality conditions for problems of the form min f(x) subject to x [euro] S. For S arbitrary we state the results in terms of cones of displacement of the feasible region at the optimal point; when S ={x ? A|g(x) ? B}, we obtain Kuhn-Tucker type results.     

基于正态分布的逐批抽样检验贝叶斯控制图控制限研究

在生产条件受控的状态下,先验分布与后验分布应服从同一分布,在假设该分布为正态分布的前提下,根据贝叶斯理论推导出均值、极差和标准差的迭代计算公式,并依此计算控制图的控制限,使有效的先验批检验信息得到充分运用,弥补传统控制图在小批量生产环境下样本信息不足的缺点。研究发现,基于贝叶斯原理的统计控制图控制限随着检验批次的逐渐增加,更接近控制界限的实际值,比传统控制图的控制效果更加可靠、有效。     

指数分布场合下步进应力加速寿命试验的Bayes分析

当寿命分布为指数分布时，本文给出了步进应力加速寿命试验的一种新的Ｂａｙｅｓ估计，为计算上的方便，本文还给出一种近似方法，数值例子表明，此方法简便可行。     

Rate of Convergence for the Empirical Distribution Function and the Empirical Characteristic Function of Mixing Processes

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Characterization of limits of Bayes procedures

For the problem of estimating the natural parameter of a p-dimensional exponential family, a characterization of regular limits of Bayes procedures is obtained which generalizes results of Sacks [14], Brown [3], and Berger and Srinivasan [1]. The form is deduced under regularity conditions for the loss function which are more general than squared error. As a corollary it is then stated that the class of procedures with this form is a complete class. The parameter space may be open, and when it is closed, the limits of Bayes procedures are generalized Bayes.     

On some multivariate density estimates and empirical Bayes problems

This paper consider estimates of multidimensional density functions and their derivatives. The asymptotic unbiasedness and the convergence properties of these estimates are established.Some applications to empirical Bayes problems are considered.     

About membership functions estimation

A logical approach to fuzzy sets method originated by Giles is developed. The infinitely many-valued logic t_ω is taken as basic. We accept, it is correct to use the strong conjunction by the logical analysis of the summation of fuzzy items. Under some broad conditions it is proved. that the sum of many fuzzy variables is a variable whose membership function is approximately equal to $\text{?(x) =}\text{max}\text{{1 ?}\text{1}\text{2}\text{c(x ? α)}{}^2\text{, 0}}$, where a and c are some constant parameters. A method of estimation of the unknown parameters is developed in a general case. The proposed fuzzy method coincides with the method of maximum likelihood if used in problems of classical mathematical statistics.