基于作业过程的园林绿化项目资源清单模型

结合生产要素六元理论，对园林绿化项目资源进行界定；以作业过程为信息关联节点，通过施工工序分解和资源特征匹配，构造园林绿化项目的“产出-作业”分配关系描述矩阵和“作业-资源”消耗关系描述矩阵。XX科技园林绿化企业的应用结果表明，项目资源清单模型解决了目前园林绿化企业资源信息分离使用的现状，是企业快速构建项目资源计划表、项目施工方案以及快速估算项目成本等的基础数据信息。     

武汉老橱窗特征解析

武汉老橱窗是当时社会生活的缩影：老橱窗是经济大潮起落的风向标,是政治风云变幻的晴雨表,是都市生活的流行时尚眼,是商店卖场的无声宣传员,是艺术空间的多彩百花园。     

Maximizing benefits in project selection: a hybrid approach

Charitable foundations and government programmes should endeavour to allocate their limited resources to best serve their constituents. Yet, mathematical programming techniques are rarely used despite overwhelming evidence of their superiority in selecting projects that yield higher levels of total benefits. We present a novel ‘hybrid selection model’ that combines binary linear programming and heuristic rank-based models applied to two case studies. The first case focuses on providing services to women and shows a hybrid model would have selected the top three ‘signature’ projects and maintained an above-average overall project benefit while securing a 180% improvement in the number of projects funded, a 66% improvement in the number of women served and a 132% improvement in the total benefit achieved. In the second case, we apply the hybrid approach to data from the US government’s largest forest preservation programme and demonstrate that the hybrid approach could allow the programme to select up to 11 top-scoring projects while still achieving a 97% gain in the total overall benefit compared to their traditional method. These case studies show that the hybrid approach has the potential to be applied in a variety of settings and improve how foundations and programmes achieve their goals.     

Robust influence diagnostics for generalized linear models with continuous responses

This article introduces two parametric robust diagnostic methods for detecting influential observations in the setting of generalized linear models with continuous responses. The legitimacy of the two proposed methods requires no knowledge of the true underlying distributions so long as their second moments exist. The performance of the two proposed influence diagnostic tools is investigated through limited simulation studies and the analyses of an illustration.     

Linear Programs in Cost Accounting： A Linear Cost Model

This paper aims to find unit cost of a product for firms. It establishes a linear cost model to find unit cost. Linear goal programs assume a direct relationship between independent variable and dependent variable. Dependent variable of linear model is unit cost. Independent variables are cost accounting variables. They are supply cost, labor cost, and administration cost. This study assumes a direct relationship between supply-labor-administration costs and unit cost. Therefore, it establishes a linear cost model. The major research question of this study is to apply linear goal programming to cost accounting. The goal of this linear program is to find unit cost of product. This study uses quantitative method and human capital method. The main research result is linear costing model itself.     

灌溉耕地空间分布制图研究进展

[目的]灌溉耕地空间分布是管理水资源、指导农业生产和监控环境变化的基础数据,遥感是获取灌溉耕地空间分布的重要手段。科学总结有关区域灌溉耕地空间分布制图的研究进展,可为遥感在该领域的应用研究提供参考。[方法]文章全面收集近年来国内外利用遥感提取灌溉耕地的文献资料,系统分析了灌溉耕地制图的特征选择和主要技术方法,并展望了未来的发展方向。[结果]从分类特征的角度看,气候、生产方式和设施等农业相关地域条件是灌溉耕地制图的必要参考;灌溉引起的水分或植被生长状况差异是主要依据;引入参量的时序变化特征或新的特征参量是对单一影像信息不完善的有效补充。从分类方法的角度看,不同分类方法多局限于局地或区域尺度,规则普适性不高,真值数据收集困难,难以适应大尺度下多样的地域条件,导致无法高效及时地生产更新相应规模且合适分辨率的产品,大区域灌溉制图的主要方式仍依赖空间分配模型。[结论]未来发展而言,自动分类技术和遥感影像资源的丰富已为高效生产灌溉分布地图提供了基础条件,整合数据资源、挖掘特征参量和优化分类方法等3个方面应是未来的主要发展方向。     

制度创新与经济增长——一个理论分析框架及实证检验

任何经济增长过程都是在一定的制度环境中进行的，有必要将制度因素纳入经济增长理论当中。在新古典经济学框架下，本文通过理论模型分析，认为稳态下的经济增长率跟制度创新有着紧密的正向关的关系。在理论分析的基础上，本文基于1978～2012年的省际面板数据，利用半参数估计和线性回归估计方法，实证分析结果表明：国家财政干预的增强、国有经济的强化和垄断作用加强从整体上抑制了我国以及不同地区的经济增长，提高市场开放度和对产权的保护程度则对经济增长产生了积极的正向促进作用，制度差异是引起我国区域经济增长差异的重要因素之一，制度创新仍是当前我国经济增长的关键。     

短期影响中国商品房房价因素的计量分析--基于31个省市的横截面数据

房价问题是影响国计民生的重要问题之一，分析房价的影响因素具有重要的现实意义。收集2012年北京、天津等31个省市相关指标的横截面数据，尝试在三种不同情况下用经典线性模型进行逐步回归拟合数据，再对不同模型进行比较，从而选出最优模型。最后，通过最优模型分析得出人均可支配收入与失业率是短期内影响中国商品房房价上涨的主要因素。     

基于特征增量的新类识别方法研究

在分类应用的过程中,经常会出现新的类别,导致数据分布发生显著变化,使得原分类模型不再适用。如何识别新的类别使分类模型能适应其出现已经成为一个亟需解决的问题。本文提出基于特征增量的SVDD(支持向量数据描述)新类识别方法。该方法在SVDD算法的基础上,通过增加新特征,扩大特征空间维度从而提高模型对于新类的识别能力。在多个数据集上的实验结果表明,该方法能有效识别新类,使更新后的模型具有更高的准确度。     

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.