基于AHP的工程投标风险模糊判定模型研究

工程投标决策对提高施工企业风险管理水平,增强企业在建筑行业的竞争能力和企业的经济效益有着重要的作用,因此必须在工程投标时要认真研究分析工程投标风险。本文在企业拟投标的工程项目中分析各种风险因素的基础上,收集信息,建立投标决策的模糊判定矩阵,并运用AHP对模型进行求解,最后判定企业是否进行投标。     

基于AHP的A公司内外因素权重选择研究

通过介绍A公司的现状并以A公司为研究对象,针对A公司今后的战略选择问题,运用层次分析法对A公司的内外因素权重进行了计算和选择;得出了A公司存在的不足和需要改进的地方,对公司自身在进行因素确定和选择提供了一种可借鉴并且可行的方法,为公司考虑物流战略或运营方式选择提供了参考.     

任意空间位置两多边形多匝线圈的互感计算

根据聂以曼公式推导出任意空间位置两多边形线圈互感的一般表达式,应用旋转矩阵实现了线圈位置的变化,通过MATLAB软件编程计算,绘出了互感的变化曲线,并对计算结果进行进行了分析验证。     

Practical Proposals for Specifying k-Nearest Neighbours Weights Matrices

Abstract

In this article, we introduce and evaluate testing procedures for specifying the number k of nearest neighbours in the weights matrix of a spatial econometric model. An increasing and a decreasing neighbours testing procedure are suggested. Kelejian's J-test for non-nested spatial models is used in the testing procedures. The testing procedures give formal justification for the choice of k, something which has been lacking in the classical spatial econometric literature. Simulations show that the testing procedures can be used in large samples to determine k. An empirical example involving house price data is provided.     

大连旅顺区土地利用及地表温度时空分异研究

伴随着城市空间的快速扩展,土地利用发生巨大转变,城市气候和生态环境问题日益突出。本文以大连旅顺区为例,基于2005年和2016年两期数据,单窗算法进行地表温度反演,并通过GIS空间分析方法,探讨旅顺区土地利用及地表温度时空分异特征。2005-2016年,旅顺区建设用地、水域面积呈增加趋势,面积分别增加了9.51 km2、13.19 km2;耕地、林草地及其他用地呈减少趋势;11年间,旅顺区地表温度整体逐渐升高;各用地的地表温度呈现出“建设用地和其他用地>耕地和园地>林草用地和水域”状态。     

No-Arbitrage ROM simulation

Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method׳s attractiveness by focusing on applications in finance. Many financial applications require simulated asset returns to be free of arbitrage opportunities. We analytically derive no-arbitrage bounds for expected excess returns to be used in the context of ROM simulation, and we establish the theoretical relation between the number of states (i.e., the sample size) and the size of (no-)arbitrage regions. Based on these results, we present a No-Arbitrage ROM simulation algorithm, which generates arbitrage-free random samples by purposefully rotating a simplex. Hence, the proposed algorithm completely avoids any need for checking samples for arbitrage. Compared to the alternative of (potentially frequent) re-sampling followed by arbitrage checks, it is considerably more efficient. As a by-product, we provide interesting geometrical insights into affine transformations associated with the No-Arbitrage ROM simulation algorithm.     

Spatial Regression Analysis vs. Kriging Methods for Spatial Estimation

Due to the rapid development of Geographic Information Systems (GIS) in recent years, spatial data analysis has received considerable attention and played an important role in social science. Although many standard statistical techniques are attractive in traditional data analysis, they cannot be implemented uncritically for spatial data. Generally, most of the studies in spatial data analysis can be divided into two branches: the model-driven approach and the data-driven approach. The main aim of this paper is the comparison of both approaches. To carry out such a task, crime rate data in Columbus (Ohio), coming from a well-known database, have been used. The main aim of this paper is to illustrate how spatial effects can be viewed as spatial econometric models, which assess the limitations of standard techniques in a spatial context, suggesting alternative methods to deal with this problem. An application to the crime rate in Columbus (Ohio) has been carried out.

Cost data quality considerations for eco-efficiency measures

Cost data are a central aspect of eco-efficiency measures, either as means to assess value of production, or, more directly, as one dimension of the efficiency ratio. Several aspects may affect the quality of cost data, among them definitions, time and space, and confidentiality issues. Somewhat surprisingly, cost data quality has received little attention in the field of sustainability and eco-efficiency so far. Even worse, perhaps, is the lack of tools suitable for a cost data quality assessment and management.This paper discusses parameters that affect cost data quality, and will then propose a pedigree matrix as a tool designed for managing cost data quality issues. The application of the matrix is described, also in combination with a previously proposed, and broadly used, pedigree matrix for environmental data quality management.     

ENHANCEMENT OF THE APPLICABILITY OF MARKOWITZ'S PORTFOLIO OPTIMIZATION BY UTILIZING RANDOM MATRIX THEORY

The traditional estimated return for the Markowitz mean-variance optimization has been demonstrated to seriously depart from its theoretic optimal return. We prove that this phenomenon is natural and the estimated optimal return is always       times larger than its theoretic counterpart, where       with  y  as the ratio of the dimension to sample size. Thereafter, we develop new bootstrap-corrected estimations for the optimal return and its asset allocation and prove that these bootstrap-corrected estimates are proportionally consistent with their theoretic counterparts. Our theoretical results are further confirmed by our simulations, which show that the essence of the portfolio analysis problem could be adequately captured by our proposed approach. This greatly enhances the practical uses of the Markowitz mean-variance optimization procedure.     

渠网非恒定流图论原理

基于明渠非恒定流普里斯曼的隐式差分方法,采用矩阵线性变换建立了渠道进出口流量与水深的线性方程。提出了新的渠网非恒定流图论原理,包括适应渠网非恒定流特征的节支关联矩阵A的构建方法及性质分析,基于A的节点连续性矩阵方程和节点水深矩阵方程等。应用矩阵分析方法,推导出渠网非恒定流的节点分析法数学模型,最后给出应用实例。