基于遗传算法的物流中心区域布置技术

对物流中心进行全参数化研究。充分考虑了区域形状,通道等实际因素,采用遗传算法解决区域布置问题,使布置结果更具实用性。     

中国数字化产业竞争力的区域差异与影响效应

本文从规模优势和发展潜力两个维度,提出数字化产业竞争力的测度方法,并以中国上市公司企业数据为基础,探讨区域层面的差异特征;利用半参数模型,从区域与行业双重层面,探究技术创新在数字化产业竞争力提升进程中的影响效应。研究发现：首先,当前中国数字化产业竞争力显著提升,但整体上呈现出由东部沿海向西部内陆递减的阶梯化分布特征,差异突出体现在规模优势层面。其次,技术创新对数字化产业竞争力的提升整体上存在倒U型影响效应,且表现出区域和行业差异。一方面,不同于东部地区,技术创新在中西部地区对数字化产业竞争力发挥着显著的正向推动作用;另一方面,不同于数字化服务业,技术创新对数字化制造业竞争力提升具有持续驱动效应。进一步分析表明,数字化制造业和数字化服务业耦合协调度处于较低的非均衡性状态。     

Measuring abnormal daily trading volume for samples of NYSE/ASE and NASDAQ securities using parametric and nonparametric test statistics

We extend prior research on the empirical properties of daily trading volume and methods to detect abnormal trading volume in two ways. We compare the performance of a nonparametric test statistic with the parametric test statistic used in prior research and we study samples of NASDAQ securities as well as samples of NYSE/ASE securities. Prior research has focused exclusively on NYSE securities. We find the nonparametric test statistic is more powerful in detecting abnormal trading volume than the parametric test statistic in both samples of NYSE/ASE and NASDAQ securities. We also document that abnormal trading volume will be detected more often in samples of NYSE/ASE securities compared to NASDAQ securities.     

Designing and evaluating sustainable development pathways for semi‐subsistence crop–livestock systems: lessons from Kenya

Achieving the Sustainable Development Goals (SDGs) in African agriculture requires a better understanding why high levels of poverty and resource degradation persist in African agriculture despite decades of policy interventions and development projects. In this article, we hypothesize that policies need to account for the key features of the semi‐subsistence crop–livestock systems (CLS) in the region to become effective. The semi‐subsistence CLS are characterized by a high degree of biophysical and economic heterogeneity and a complex, diversified production system involving a combination of subsistence and cash crops with livestock. We investigated the potential for interventions proposed by the Government of Kenya to meet the SDGs by 2030. The analysis uses an integrated modeling approach designed to deal with the key features of these systems. A strategy that stimulates rural development, increases farm size to a sustainable level, and reduces distortions and inefficiencies in input and output markets could lead to a sustainable development pathway and achieve the SDGs for rural households dependent on CLS.     

An adaptive approach to forecasting three key macroeconomic variables for transitional China

The macroeconomic forecasts for emerging economies often suffer from the constraints of instability and limited data. In light of these constraints, we propose the use of a local autoregressive (LAR) model with a data-driven estimation window, i.e., a local homogenous interval, that is adaptively identified to strike a balance between information efficiency and stability. When applied to three key macroeconomic variables of China, the LAR model substantially outperforms the alternative models for various forecast horizons of 3 to 12 months, with forecast error reductions of between 4% and 64% for the IP growth, and between 1% and 68% for the inflation rate. The one-quarter ahead performance of the LAR model matches that of a well-known survey forecast. The patterns of the identified local intervals also coincide with the characteristic evolution of the gradual reforms and monetary policy shifts in China. In short, the LAR model is suitable for not only forecasting, but also the real-time monitoring of the effects of regime and policy changes in emerging economies.     

REGULATION STRATEGIES FOR THE PROVISION OF PATERNALISTIC GOODS

In this study, we analyze the regulation of markets for the provision of services whose costs are subsidized for paternalistic reasons. We model the choice of a benevolent regulator who wants to maximize consumer welfare in a setting where quality cannot be verified and the good provided is fully subsidized. The choice is thus made between two types of providers (profit maximizers and altruistic providers) and two frameworks (monopoly franchise and quality competition). Our analysis shows that in this environment the performance of mixed markets is always dominated by pure forms. Moreover, although making efficient providers compete for the market minimizes cost, the choice of quality competition with altruistic providers may be preferable from a welfare point of view whenever service quality is relevant and the productivity differential is not substantial.     

智慧BIM乔木模型：从设计图纸到施工 现场

现有的BIM应用软件提供的乔木模型多为RPC或高 精度3D模型等3D CAD类型。这些模型着重于表达美感或进 行展示，无法反映根系情况。虽然可能包含一定附加属性，但 表达乔木生长和空间需求的功能有限。因而，冲突检查、工序 调度等BIM的优势功能无从应用。风景园林实践领域已就此问 题开始构建自己的模型库，但能够准确反映现状树木真实尺寸 体量，以及现状树木和规划树木未来空间需求的模型仍未广泛 出现。提出一种基于树冠、树干和根系构型与生长功能的实体/ 网面封装建模方法构建BIM乔木模型。模型形态通过一组参数 调整，并根据树龄和反映环境限制因子的值来反映其变化。所 包含的数据和参数数量随后期设计阶段所需的LoD(详细层级) 及专业实践的具体要求而增加。该模型可以与提供本地区内外 苗木商品信息的植物数据库连接使用。     

Extreme Value Theory and Statistics of Univariate Extremes: A Review

Statistical issues arising in modelling univariate extremes of a random sample have been successfully used in the most diverse fields, such as biometrics, finance, insurance and risk theory. Statistics of univariate extremes (SUE), the subject to be dealt with in this review paper, has recently faced a huge development, partially because rare events can have catastrophic consequences for human activities, through their impact on the natural and constructed environments. In the last decades, there has been a shift from the area of parametric SUE, based on probabilistic asymptotic results in extreme value theory, towards semi‐parametric approaches. After a brief reference to Gumbel's block methodology and more recent improvements in the parametric framework, we present an overview of the developments on the estimation of parameters of extreme events and on the testing of extreme value conditions under a semi‐parametric framework. We further discuss a few challenging topics in the area of SUE. © 2014 The Authors. International Statistical Review © 2014 International Statistical Institute     

Methods for Scalar‐on‐Function Regression

Recent years have seen an explosion of activity in the field of functional data analysis (FDA), in which curves, spectra, images and so on are considered as basic functional data units. A central problem in FDA is how to fit regression models with scalar responses and functional data points as predictors. We review some of the main approaches to this problem, categorising the basic model types as linear, non‐linear and non‐parametric. We discuss publicly available software packages and illustrate some of the procedures by application to a functional magnetic resonance imaging data set.