基于灰色模糊的变电站建设效益评价模型

投资效益是变电站建设决策的主要指标.本文从变电站建设所产生的影响入手,对各种效益评价因素进行了详细的归纳和汇总,形成一套完全的变电站建设效益评价指标体系.并运用灰色模糊评判理论对投资效益进行评判.通过变电站选址实例,证明该指标体系和评价模型能很好地应用于变电站建设决策.     

企业竞争力的一种评价方法

讨论了企业竞争力的一种模糊评价方法,归纳了影响竞争力评价的因素。给出了一种应用于企业竞争力评价的指标体系和模糊评价方法,运用主成分分析法确定各指标的权重,为企业竞争力评价提供了一种定量分析方法。     

西部地区循环经济评价指标体系及实证研究

构建了西部地区循环经济指标体系的一级、二级指标,确定了各项指标的权重、标准值以及综合评价方法;运用该指标体系和评价方法对西部地区的循环经济发展现状进行测算,结果表明：西部地区循环经济发展水平不高且发展不平衡。     

模糊熵值法在项目投资决策中应用

结合投资项目决策的特点,系统地分析了项目投资方案决策的主要影响因素,提出了方案评价的指标体系。运用模糊数学的相关理论及其应用,建立了方案决策的多目标模糊优选模型,并用熵值法确定了各指标的评价权重值。通过实例分析说明模型是可行的。     

火电投资项目社会评价研究

本文根据火电项目有关技术经济数据,确定了火电项目社会评价的指标体系,运用模糊数学理论建立了火电项目社会评价模型和评价指标的隶属函数、提出了火电项目社会评价的模糊评价方法。     

装配式建筑施工风险评价

基于对五类风险因素的分析建立装配式建筑施工风险评价指标体系,引入G1—熵权组合赋权的方法确定风险指标的权重。结合灰色聚类与模糊综合评价法,构建装配式建筑施工风险灰色模糊综合评价模型。最后运用实证进行分析,验证此模型的可行性与合理性。     

基于AHP-FCE的氯碱化工园区循环经济评价研究

结合氯碱化工园区的实际情况,建立了氯碱化工园区循环经济评价指标体系,运用层次分析法(analytical hierarchy process,AHP)确定了指标体系中各指标的权重,运用模糊综合评判(fuzzy com prehensive evaluation,FCE)理论,建立了氯碱化工园区循环经济综合评价模型,并将这一模型应用于某氯碱化工园区循环经济的综合评价。实例表明:模糊综合评价方法可操作性强,可在氯碱化工园区循环经济综合评价中广泛应用。     

基于层次分析法的高层建筑施工现场火灾风险模糊评价

针对高层建筑施工现场的火灾风险评价问题,在对各因素相互关系进行分析的基础上,通过层次分析法建立了由防火能力、灭火能力、疏散逃生能力和消防安全管理四大子系统组成的火灾风险评价指标体系,确定了指标体系内各因素的权值分配,得到了针对高层建筑施工现场的火灾风险评价模型。运用模糊综合评价方法对实际工程进行评价,根据最大隶属度原则确定了该工程的火灾风险等级。通过对评价结果的分析,找出了高层建筑施工现场存在的火灾隐患以及消防安全管理薄弱环节,提出了改进对策,指导施工人员有效控制施工中的不安全因素,减少施工中火灾事故的发生。     

煤矿应急管理能力二级模糊综合评价及对策建议

依据《中华人民共和国突发事件应对法》,基于4R理论,从准备与预防、监测与预警、应急与救援、事后恢复等方面确定侧重应急管理全过程的25个指标的评价指标体系。咨询多家煤炭企业和多名权威专家,利用层次分析法确定各指标的权重并进行一致性验算。选取淮北煤矿集团公司某矿作为评价案例,利用模糊综合评价法对该矿应急管理能力进行评价,验证指标体系的可行性。根据评价结果,查找该矿四个一级指标中评分较低的二级影响因素,并提出对策建议。     

公路工程质量评价模式研究

公路工程质量评价作为实施公路工程质量管理的重要手段,是发现存在问题、寻找改进方法、提高工程质量的依据。笔者根据评价对象的特点,同时考虑了影响公路质量的所有定量与定性因素,构建了公路工程评价指标体系,并采用客观问卷调查与层次分析法相结合的方法确定了指标体系的权重。指标权重反映了影响公路工程质量的各项因素的重要程度,可为公路工程管理部门决策提供参考。     

Surpluses in Disequilibrium Urban Land Markets

It is unlikely that urban land markets are in equilibrium. If land markets are out of equilibrium, zones within an urban area would have residential location surpluses. This paper shows how to derive and estimate an index of income surplus by residential zone. The procedure is applied to the Baltimore Metropolitan Area for 1978. Households should be at attracted to zones with high surpluses. A comparison of the estimated location surpluses and growth rates for the Baltimore area show this correspondence.     

Transportation, Sorting and House Values

In this paper, we examine the importance of accessibility to employment and transportation system attributes for residential location choice, car ownership and house values. Using the 1980 Census of Housing and Journey to Work data merged with transportation system data, we find strong evidence of residential sorting based on employment location. We find that suburban areas with good commuter rail access to the CBD have significantly greater fractions of their labor force working in the CBD, own fewer cars and have higher house prices than similar neighborhoods and houses in census tracts without service. The house value premium is over 6.4%.     

Modeling Spatial Variation in Housing Prices: A Variable Interaction Approach

The absolute location of each real estate parcel in an urban housing market has a unique location-value signature. Accessibility indices, distant gradients and locational dummies cannot fully account for the influence of absolute location on the market price of housing because there are an indeterminable number of externalities (local and nonlocal) influencing a given property at a given location. Furthermore, the degree to which externalities affect real estate values is not only unique at each location but highly variable over space. Hence, absolute location must be viewed as interactive with other determinants of housing value. We present an interactive variables approach and test its ability to explain price variations in an urban residential housing market. The statistical evidence suggests that the value of location, as embodied in the selling price of housing units, may not be separable from other determinants of value. It is recommended that housing valuation models, therefore, be specified to allow site, structural and other independent attributes to interact with absolute location—{ x , y } coordinates—when accounting for intraurban variation in the market price of residential housing. This approach is especially useful when estimating the value of housing for geographic areas where very little is known a priori about the neighborhoods or submarkets.     

A Comparative Anatomy of Residential REITs and Private Real Estate Markets: Returns,Risks and Distributional Characteristics

Real Estate Investment Trusts (REITs) are the only truly liquid assets related to residential real estate investments. We study the behavior of U.S. Residential REITs over the past three decades and document their return characteristics. REITs have somewhat less market risk than equity; their betas against a broad market index average about 0.58. Decomposing their covariances into principal components reveals several strong factors. Residential REIT characteristics differ to some extent from those of the S&P/Case‐Shiller (SCS) private real estate markets. This is partly attributable to methods of index construction. Our examination of REITs suggests that investment in residential real estate is far more risky than what might be inferred from the widely followed SCS series. Although the SCS and REITs indicate little support for being able to predict each other, there is strong evidence of self‐predictability for the series.     

基于Hedonic模型的小区房价影响因素研究——以南京市鼓楼区为例

从小区房价的微观影响因素出发,分别从建筑特征、邻里特征、区位特征三个方面确定了10个特征价格变量,运用定量和定性相结合的方法,构建影响南京市鼓楼区小区房价的特征价格模型,并对回归结果进行检验和分析。结果表明:建筑年代、容积率、交通干道等级是影响小区房价弹性的最大因素;主要街道等级是影响小区房价的最主要微观因素。希望通过本文研究给房地产开发商、政府、消费者等在决策和选择上提供借鉴。     

Statistical Approaches to Forecasting Domestic Energy Consumption and Assessing Determinants: The Case of Nordic Countries

The residential sector accounts for large share of total annual energy use in the Nordic countries due to the extremely cold climates and high household heating demand. Most domestic energy consumption in the Nordic countries is for space heating and providing hot water. The purpose of our study was to forecast the annual energy consumption of the Nordic residential sectors by 2020 as a function of socio-economic and environmental factors, and to offer a framework for the predictors in each country.

Our research models the domestic energy use in Nordic countries based on social, economic and environmental factors. Applying the multiple linear regression (MLR), multivariate adaptive regression splines (MARS), and the artificial neural network (ANN) analysis methodologies, three models have been generated for each country in the Nordic region. Using these models, we forecasted the Nordic countries domestic energy use by 2020 and assessed the causal links between energy consumption and the investigated predictors. The results showed that the ANN models have a superior capability of forecasting the domestic energy use and specifying the importance of predictors compared to the regression models. The models revealed that changes in population, unemployment rate, work force, urban population, and the amount of CO₂ emissions from the residential sectors can cause significant variations in Nordic domestic sector energy use.     

Which Are The Main Drivers Behind Residential Electricity Prices?

Over the last decade the residential electricity price in most EU Member States has been increasing. Even after the introduction of significant reforms such as the liberalisation of the electricity market. This upward trend is in response to the development of different price components along the electricity supply chain. In order to identify and analyse these components for EU-Member States, a more detailed price apportionment than those offered by public sources like Eurostat and IEA is necessary. The methodology proposed in this study analyses the development of the residential electricity price and its main components between 2002 and 2012 for Germany, France, Italy and the United Kingdom. The main drivers of the price trends observed for these four countries are subsequently identified, quantified and compared. Furthermore, the residential expenditure on electricity in each country is examined in connection with the evolution of residential electricity consumption. The results show how and to what extent the residential electricity price for the selected EU Member States depends on price components such as the electricity wholesale price, the gross margin, network expenditures, energy taxes and other levies related to the decarbonisation of the national energy system. Furthermore, this detailed analysis of residential electricity prices throughout the last decade provides a sufficient data basis to draw some prospective conclusions in terms of a short-term price outlook.     

Task‐based structures in open source software: revisiting the onion model

Studies on Open Source Software (OSS) developer communities have long stated that there is a relationship between community structure and tasks carried out by project members. This relationship has been exemplified by the onion model, which has been instrumental in understanding self‐coordination in OSS projects. Despite its ubiquity, there is a lack of empirical evidence to validate the relative position of each task cluster within the onion model. In this study, we map out the community structure of a large open source project and observe its bug‐fixing patterns to explore the relationship between tasks and structure. Our study makes three significant contributions. First, we find no empirical evidence to support the structural location of bug‐fixing tasks in the onion structure. Second, we find empirical evidence to support the core‐periphery continuum model linking an actor’s coreness to problem‐solving ability. Third, our results suggest that the importance and location of each task within the core‐periphery structure evolve over time. These findings add clarity to the community structure and their implications for the management and coordination of collaborative innovation projects.     

Development of a Network-location-model for the Economic Optimization of Local Heating Systems in Urban Chile

Cogeneration of heat and electricity is an important pillar of energy and climate policy. To plan the production and distribution system of combined heat and power (CHP) systems for residential heating, suitable methods for decision support are needed. For a comprehensive feasibility analysis, the integration of the location and capacity planning of the power plants, the choice of customers, and the network planning of the heating network into one optimization model are necessary. Thus, we develop an optimization model for electricity generation and heat supply. This mixed integer linear program (MILP) is based on graph theory for network flow problems. We apply the network location model for the optimization of district heating systems in the City of Osorno in Chile, which exhibits the “checkerboard layout” typically found in many South American cities. The network location model can support the strategic planning of investments in renewable energy projects because it permits the analysis of changing energy prices, calculation of break-even prices for heat and electricity, and estimation of greenhouse gas emission savings.     

住宅小区人居环境评价指标体系研究

通过对人居环境概念的分析，探讨了人居环境的标准及其评价指标体系建立的基本原则，在此基础上建立了相应的评价指标体系，给出了评价的方法和具体流程。