网络环境对财务风险预警系统的影响

近年来，随着网络在财务管理工作中的应用，财务风险发生了显著的变化。建立网络环境下的财务风险预警系统已经迫在眉睫。我国对这一领域的研究无论在理论上还是在实践上都较薄弱，财务预警管理也是我国企业迫切需要解决的问题。     

Multivariate outliers and decompositions of mahalanobis distance

Two decompositions of the Mahalanobis distance are considered. These decompositions help to explain some reasons for the outlyingness of multivari- ate observations. They also provide a graphical tool for identifying outliers including those that have a large influence on the multiple correlation coefficient, Illustrative examples are given.     

强化学习型匝道控制模型的研究

高速公路上的交通堵塞造成了道路利用效率低下，并伴随着能源消耗和环境污染问题，因此各种各样的高速公路控制方法应用于缓解交通堵塞。本文提出强化学习型匝道控制模型，该模型以交通流模拟为预测工具，以人工智能的强化学习为最优化选择模型，并具有一定的自主性、有记忆功能和性能反馈功能，且是一种动态的过程。应用JAVA针对不同的交通状态进行模拟再现，模拟结果表明匝道控制模型对于减少交通堵塞具有显著的效果。     

Contrasting the Gini and Zenga indices of economic inequality

The current financial turbulence in Europe inspires and perhaps requires researchers to rethink how to measure incomes, wealth, and other parameters of interest to policy-makers and others. The noticeable increase in disparities between less and more fortunate individuals suggests that measures based upon comparing the incomes of less fortunate with the mean of the entire population may not be adequate. The classical Gini and related indices of economic inequality, however, are based exactly on such comparisons. It is because of this reason that in this paper we explore and contrast the classical Gini index with a new Zenga index, the latter being based on comparisons of the means of less and more fortunate sub-populations, irrespectively of the threshold that might be used to delineate the two sub-populations. The empirical part of the paper is based on the 2001 wave of the European Community Household Panel data set provided by EuroStat. Even though sample sizes appear to be large, we supplement the estimated Gini and Zenga indices with measures of variability in the form of normal, t-bootstrap, and bootstrap bias-corrected and accelerated confidence intervals.     

Adaptive agent-based manufacturing control and its application to flow shop routing control

The manufacturing industry is currently facing unprecedented challenges from changes and disturbances. The sources of these changes and disturbances are of different scope and magnitude. They can be of a commercial nature, or linked to fast product development and design, or purely operational (e.g. rush order, machine breakdown, material shortage etc.). In order to meet these requirements it is increasingly important that a production operation be flexible and is able to adapt to new and more suitable ways of operating. This paper focuses on a new strategy for enabling manufacturing control systems to adapt to changing conditions both in terms of product variation and production system upgrades. The approach proposed is based on two key concepts: (1) An autonomous and distributed approach to manufacturing control based on multi-agent methods in which so called operational agents represent the key physical and logical elements in the production environment to be controlled – for example, products and machines and the control strategies that drive them and (2) An adaptation mechanism based around the evolutionary concept of replicator dynamics which updates the behaviour of newly formed operational agents based on historical performance records in order to be better suited to the production environment. An application of this approach for route selection of similar products in manufacturing flow shops is developed and is illustrated in this paper using an example based on the control of an automobile paint shop.     

一种榫卯连接方钢管组装框架模型的荷载 位移曲线试验研究

提出一种榫卯连接方钢管组装框架结构。对两个方向的平面框架模型进行受力性能试验。介绍试验概况，给出框架模型的竖向荷载与挠度和水平荷载与水平侧移曲线，这些曲线介于刚节点框架和铰节点框架之间，属于半刚性节点框架的范畴。     

General m-esttmators and applications to bounded influence estimation for non-linear regression

In this paper, we study the M-estimators in the case that λ_F:(β)=E_F:(φ(Z,β))=0 has more than one solution, We show that the numerical iterative procedures converge and that the resulting estimators are consistent and asymptotically normal. We apply them to the non-linear regression models, and then, we find an optimal M-estimate among those that have bounded gross error sensitivity.     

Asymptotic robustness of least median of squares for autoregressions with additive outliers

This paper considers the robustness properties in the time series context of the least median of squares (LMS) estimator. The influence function of the LMS estimator is derived under additive outlier contamination. This influence function is redescending and bounded for fixed values of the AR parameters. The gross-error sensitivity, however, is an unbounded function of the AR parameters. In order to asses the global robustness behavior of the LMS estimator, we consider several notions of breakdown. The breakdown points of the LMS estimator depend on the value of the underlying AR parameter. Generally, the breakdown point is below one half for high values of the AR parameter. The bias curves of the LMS estimator reveal, however, that the magnitude of outliers has to be considerable in order to cause breakdown.     

Improving traceability in continuous processes using flow simulations

Traceability is normally difficult to achieve in continuous processes, since there are no natural batch structures. In this article, we demonstrate flow-based simulation using process data to improve traceability in a continuous pelletising process. Using the simulation model, the engineers could test the impacts of process disturbances, identify cause and effect relations and aid control in case of process disturbances. In a field trial where the chemistry of an additive was varied during production of a special product, the simulation forecasts predicted the level of the chemical content after the plant within the errors that the engineers found acceptable.     

Further influence measures in factor analysis

Various influence measures are discussed for sensitivity analysis in factor analysis. The internal norm is used to characterize the vector-valued influence curves in factor analysis. Influence curves for the chi-square goodness of fit test, and the determinants of the model covariance matrix and unique variance matrix are derived. They are found to have simple formulas which are easy to be interpreted and have nice distributions for calibration. The likelihood displacement is also applied to sensitivity analysis in maximum likelihood factor analysis.