Zero weights and non-zero slacks: Different solutions to the same problem

This paper re-assesses three independently developed approaches that are aimed at solving the problem of zero-weights or non-zero slacks in Data Envelopment Analysis (DEA). The methods are weights restricted, non-radial and extended facet DEA models. Weights restricted DEA models are dual to envelopment DEA models with restrictions on the dual variables (DEA weights) aimed at avoiding zero values for those weights; non-radial DEA models are envelopment models which avoid non-zero slacks in the input-output constraints. Finally, extended facet DEA models recognize that only projections on facets of full dimension correspond to well defined rates of substitution/transformation between all inputs/outputs which in turn correspond to non-zero weights in the multiplier version of the DEA model. We demonstrate how these methods are equivalent, not only in their aim but also in the solutions they yield. In addition, we show that the aforementioned methods modify the production frontier by extending existing facets or creating unobserved facets. Further we propose a new approach that uses weight restrictions to extend existing facets. This approach has some advantages in computational terms, because extended facet models normally make use of mixed integer programming models, which are computationally demanding.     

基于SPA的双枝模糊决策分析

将集对理论(SPA)与双枝模糊决策理论相结合,用集对分析的方法研究进行双枝模糊决策的方法,分别对双枝模糊决策因素域和双枝模糊决策的上枝、下枝和双枝进行了集对分析,给出了用SPA进行双枝模糊决策的性质,同时讨论了双枝模糊决策的动态分析方法,以及双枝模糊决策度强弱态势预测的方法,从而为双枝模糊决策理论的研究提供了新的视角和方法,为双枝模糊决策的应用提供了更方便的工具和更强的理论支持。     

深亚微米集成电路的快速时域仿真技术

随着深亚微米集成电路技术的发展，集成电路的规模越来越大，工作频率越来越高，并正朝着系统集成的方向发展，因而在模拟速度，模拟精度和可模拟的电路规模等各个方面对电路仿真技术提出了新的要求。近年来，各种新的电路仿真方法和仿真系统用相继脱颖百出，并将取代那些传统的，已经无法适应深亚微米技术发展的电路仿真器。     

河南省城市居民消费结构比较研究

本文主要应用聚类分析方法 ,对河南省 17个地市级城市居民的消费结构进行了比较统计分析 ,从而得到了各城市居民消费结构的一些特点和规律 ,并进一步探讨了其消费结构、可支配收入与总消费支出之间的关系     

一种区间数的因子分析技术及其在证券市场中的应用

传统的因子分析技术能够有效地对高维变量空间进行降维处理,但它对于样本空间却缺乏行之有效的降维效果.为了解决这一问题,一种针对大量样本数据、新的因子分析技术———区间数因子分析技术(intervaldatafactoranalysis,IFA)被提出并得到了迅速的发展。IFA方法对传统的数据概念做了本质性的扩张,运用'数据打包'的理念,对海量原始数据在不破坏其原有内在逻辑关系的前提下,可以进行变量和样本点维度的双重降维。本文详细阐述了区间数因子分析技术的原理,并以中国股票市场为案例研究背景,结果表明IFA分析技术对大规模多维数据系统做综合简化是十分有效的。     

因子分析在企业竞争力评价中的应用

根据因子分析原理,建立了企业竞争力的规模因子、效益因子和成长因子得分模型。通过现实竞争力和潜在竞争力分析,实现了企业竞争力和可持续发展的评价。     

周期分析法在棉红蜘蛛发生程度预测中的应用

本文应用周期分析方法对江陵县棉红蜘蛛—朱砂叶螨的预测预报技术作了新的尝试．经对江陵县３６年历史资料拟合，符合率高达９４．４％．运用这一技术对该县１９８７—１９９６年棉红蜘蛛发生程度进行了１０年长期预测预报．     

光电光谱法分析钢中钙

本文研究了用光电光谱法测定钢中钙的方法 ,确定了最佳分析条件 ,分析了共存元素的干扰情况。用本方法测定钢中钙 ,具有良好的准确度和精密度 ,结果令人满意。     

一类广义Lanchester模型的数值解及若干结论

本讨论了一类广义的Lanchester模型在一些限制条件下的近似解，并给出了若干结论。     

Extension of multivariate regression trees to interval data. Application to electricity load profiling

Summary  Several data can be presented as interval curves where intervals reflect a within variability. In particular, this representation is well adapted for load profiles, which depict the electricity consumption of a class of customers. Electricity load profiling consists in assigning a daily load curve to a customer based on their characteristics such as energy requirement. Within the load profiling scope, this paper investigates the extension of multivariate regression trees to the case of interval dependent (or response) variables. The tree method aims at setting up simultaneously load profiles and their assignment rules based on independent variables. The extension of multivariate regression trees to interval responses is detailed and a global approach is defined. It consists in a first stage of a dimension reduction of the interval response variables. Thereafter, the extension of the tree method is applied to the first principal interval components. Outputs are the classes of the interval curves where each class is characterized both by an interval load profile (e.g. the class prototype) and an assignment rule based on the independent variables.