一种改进的全局可靠性分析方法

基于Kriging模型的高效全局可靠性分析(EGRA)方法在每次循环迭代过程中只能增加一个样本点.为了提高EGRA方法的效率，提出了一种基于多代理模型的改进全局可靠性分析算法.通过引入Kriging模型的预测误差，在每次循环迭代过程中，计算多个代理模型的期望可行函数(EFF)获得多个最佳样本点，将这些样本点同时加入到样本库中并更新所有代理模型，直到满足给定的精度为止.在建立极限状态函数高质量的近似模型后，采用蒙特卡罗方法进行可靠性分析.两个数值算例的分析结果表明，该方法具有较高的效率和准确性.     

等厚干涉中非等精度测量的不确定度分析

综合考虑牛顿环实验中牛顿环的直径、入射光的波长以及测量不规范等三个因素对透镜曲率半径的影响,推导出总不确定度的解析式。分别利用两种方法对不确定度做了计算,在精确度要求不高的情况下,给出了一种较简易的非等精度测量的不确定度处理方法。     

三种常用方法处理实验数据不确定度评定的讨论

以伏安法测电阻为例，分别用作图法、逐差法、最小二乘法对实验数据进行了处理，并比较了这三种常用的处理实验数据方法的不确定度的评定．     

Stochastic comparisons in a price-quantity setting firm with uncertain demand and emergency procurement

We consider a newsvendor problem with price-dependent demand, in either additive or multiplicative format. The newsvendor has two modes of purchasing： regular ordering at the beginning of the selling season and emergency ordering （if the realized demand exceeds the initial order quantity） at the end of the selling season. By stochastic comparisons, we systematically investigate the effects of demand magnitude and demand randomness on pricing and ordering quantity decisions as well as expected profit of the newsvendor, under both usual stochastic order （first order stochastic dominance） and convex order （less variable）. Our key findings include： （i） in contrary to the case where price is exogenous, a stochastically larger demand shock may even lead to a lower order quantity; （ii） a stochastically larger demand shock leads to a higher price for the additive demand case, but may lead to a lower price for the multiplicative demand case; （iii） a stochastically larger demand shock leads to a higher expected profit for both demand models; （iv） in general, a less variable demand leads to a higher expected profit for both demand models; and furthermore, a less variable demand shock has no effect on price for the additive demand model, but leads to a higher price for the multiplicative demand model. The implications of all these findings for pricing and order quantity are discussed in detail.     

基于云遗传算法的不确定性环境下平台资源调度适应性优化方法

针对战场环境中不确定因素对平台资源调度方案的影响,提出了一种面向不确定事件的平台资源调度适应性优化方法。考虑平台损耗和任务处理时间2个方面的不确定性,建立以最大任务执行效率为目标函数的平台资源调度的适应性优化问题的数学模型,根据不确定事件对平台资源能力或任务属性的影响来判断是否触发调度方案的适应性优化,并基于云遗传算法设计了平台资源调度适应性优化问题数学模型的求解方法,最后通过算例进行了验证。仿真结果表明,使用云遗传算法对平台资源调度方案进行适应性优化调整,能得到更加优化的平台任务匹配关系,并从整体上缩短使命完成时间。     

Fuzzy-Expert Diagnostics for Detecting and Locating Internal Faults in Three Phase Induction Motors

Internal faults in three phase induction motors can result in serious performance degradation and eventual system failures if not properly detected and treated in time. Artificial intelligence techniques, the core of soft-computing, have numerous advantages over conventional fault diagnostic approaches; therefore, a soft-computing system was developed to detect and diagnose electric motor faults. The fault diagnostic system for three-phase induction motors samples the fault symptoms and then uses a fuzzy-expert forward inference model to identify the fault. This paper describes how to define the membership functions and fuzzy sets based on the fault symptoms and how to construct the hierarchical fuzzy inference nets with the propagation of probabilities concerning the uncertainty of faults. The designed hierarchical fuzzy inference nets efficiently detect and diagnose the fault type and exact location in a three phase induction motor. The validity and effectiveness of this approach is clearly shown from obtained testing results.     

HPLC法测定片剂中双氢青蒿素含量的不确定度评估

分析HPLC法测定双氢青蒿素哌喹片中双氢青蒿素含量的不确定度构成及其大小。通过对不确定度分量进行分析和评定,计算含量测定中各条件的合成不确定度和扩展不确定度。最终得出扩展不确定度U=0.8 mg(k=2)。HPLC法测定双氢青蒿素哌喹片中双氢青蒿素含量的不确定度评估中供试品溶液色谱峰面积所引起的不确定度分量对合成不确定度影响最大。     

半连续模糊映射的性质

利用模糊数参数形式的概念,重新定义由Bao和wu提出的上下半连续映射的概念．在由Goetschel和Voxman提出的模糊数的线性准则基础上,证明了在n维欧式空间R^n的一个非空开区间里,存在一个有界闭集,使得上半连续模糊映射是有界的;同样的在n维欧式空间R^n的一个非空开区间里,存在一个有界闭集,使得下半连续模糊映射是有界的．     

非线性中立型泛函微分方程正解的迭代逼近

利用Banach压缩映象原理,得到下列一阶非线性中立型泛函微分方程[x(t)+a(t)x(t-τ(t))]′+f(t,x(t-σ1),x(t-σ2),…,x(t-σn))=0无穷多个有界正解的存在性.此外,还给出了这些有界正解的迭代逼近序列以及相应的误差估计.文章结果推广并改进了已有文献中的相应结果.     

向量优化中Arrow-Barankin-Blackwell稠密性定理的评注

 真有效点集在Pareto有效点集中的Arrow-Barankin-Blackwell稠密性理论是向量优化理论的组成部分,已被广泛研究并获得了一系列深刻的结果.该文就弱紧凸集和紧凸集概述了正真有效点集在Pareto点集中的稠密性,并就弱紧非凸集介绍了超有效点集在Pareto点集中的稠密性.