集成化供应链绩效评价方法研究

提出了一种基于客户服务水平的集成化供应链绩效评价的区间数线性规划方法。通过引入系数a,将区间数线性规划问题转化为参数线性规划问题,使评价方法能够反映实现客户服务承诺效用的大小,其评价过程更具柔性,并通过实例分析了该方法的应用效果。研究结果表明,多客户服务是企业所在的供应链之间竞争的焦点,处于集成化供应链响应市场需求的关键环节,而基于客户服务水平的集成化供应链绩效评价能较准确地反映供应链整体绩效,具有重要的参考价值。     

设计介入空、间——从一般设计空间观念说开去

一般的设计空间观念将空间理解成浑然的、客观的存在状态,从而导致空间研究的闭塞与若干关系的隔绝。建立多元、开放的空间体系,使设计真正地介入空间是设计学研究的目标之一。     

一种基于IEEE 802.11 PSM的增强节能机制

分析了IEEE802.11分布式协调功能的能量节省机制,针对其采用一种固定信号时隙的局限性,提出了一种自适应节能机制。新机制采用三种信号时隙,由节点根据自己的数据流量动态选择其中一种。仿真结果表明,此机制在保持较高的吞吐量的同时,不仅大幅地提高了能量利用率,还明显地降低了时延。     

参数型非空交定理和拓扑Riesz空间中的极大极小定理

本文首先证明了区间空间上的几个参数型非空交定理,并由此得到拓扑Riesz空间中的几个新型极大极小定理,本文的结果包含[1、5、6]中主要结果为特例。     

Smoothing spline Gaussian regression: more scalable computation via efficient approximation

Summary.  Smoothing splines via the penalized least squares method provide versatile and effective nonparametric models for regression with Gaussian responses. The computation of smoothing splines is generally of the order O ( n ³), n being the sample size, which severely limits its practical applicability. We study more scalable computation of smoothing spline regression via certain low dimensional approximations that are asymptotically as efficient. A simple algorithm is presented and the Bayes model that is associated with the approximations is derived, with the latter guiding the porting of Bayesian confidence intervals. The practical choice of the dimension of the approximating space is determined through simulation studies, and empirical comparisons of the approximations with the exact solution are presented. Also evaluated is a simple modification of the generalized cross-validation method for smoothing parameter selection, which to a large extent fixes the occasional undersmoothing problem that is suffered by generalized cross-validation.     

Covariate Adjusted Correlation Analysis via Varying Coefficient Models

Abstract.  We propose covariate adjusted correlation (Cadcor) analysis to target the correlation between two hidden variables that are observed after being multiplied by an unknown function of a common observable confounding variable. The distorting effects of this confounding may alter the correlation relation between the hidden variables. Covariate adjusted correlation analysis enables consistent estimation of this correlation, by targeting the definition of correlation through the slopes of the regressions of the hidden variables on each other and by establishing a connection to varying-coefficient regression. The asymptotic distribution of the resulting adjusted correlation estimate is established. These distribution results, when combined with proposed consistent estimates of the asymptotic variance, lead to the construction of approximate confidence intervals and inference for adjusted correlations. We illustrate our approach through an application to the Boston house price data. Finite sample properties of the proposed procedures are investigated through a simulation study.     

Fuzzy区间值函数项级数及其一致收敛性

文章在已知Fuzzy函数项级数一致收敛概念的基础上,补充了区间值函数项级数一致收敛的概念和判别方法,给出了一致收敛性的区间值函数项级数的分析性质。     

Bayesian sample-size determination for one and two Poisson rate parameters with applications to quality control

We formulate Bayesian approaches to the problems of determining the required sample size for Bayesian interval estimators of a predetermined length for a single Poisson rate, for the difference between two Poisson rates, and for the ratio of two Poisson rates. We demonstrate the efficacy of our Bayesian-based sample-size determination method with two real-data quality-control examples and compare the results to frequentist sample-size determination methods.     

Confidence Intervals Based on Local Linear Smoother

Point-wise confidence intervals for a non-parametric regression function in conjunction with the popular local linear smoother are considered. The confidence intervals are based on the asymptotic normal distribution of the local linear smoother. Their coverage accuracy is evaluated by developing Edgeworth expansion for the coverage probability. It is found that the coverage error near the boundary of the support of the regression function is of a larger order than that in the interior, which implies that the local linear smoother is not adaptive to the boundary in terms of coverage. This is quite unexpected as the local linear smoother is adaptive to the boundary in terms of the mean squared error.     

Nonparametric estimation of the limiting availability

The point availability of a repairable system is the probability that the system is operating at a specified time. As time increases, the point availability converges to a positive constant called the limiting availability. Baxter and Li (1994a) developed a technique for constructing nonparametric confidence intervals for the point availability. However, nonparametric estimators of the limiting availability have not previously been studied in the literature. In this paper, we consider two separate cases: (1) the data are complete and (2) the data are subject to right censorship. For each case, a nonparametric confidence interval for the limiting availability is derived. Applications and simulation studies are presented.deceased after the paper was accepted