我国城市化进程定量评价及影响因素分析

为深入研究城市化质量问题,从经济、社会、人口、生态四个方面构建了城市化评价指标体系,并根据所构建的城市化评价指标体系,从国家统计年鉴中选取43类指标来评价1995年到2010年我国城市化进程的发展水平,以因子分析法为基础,构建了城市进程发展指数,对我国城市化进程的持续性和影响因素进行了定量评价。研究显示:工业和第三产业是我国城市化的主要动力,同时,在医疗教育、能源利用方面仍有待提高。     

国防科研院所项目管理能力评价指标体系的构建研究

根据国防科研院所项目管理的特点,依据项目管理评价指标体系设置原则和项目管理知识体系,提出国防科研院所项目管理能力评价指标,并采用模糊偏好关系群决策的原理和方法对指标进行筛选,建立国防科研院所项目管理能力评价指标体系。在此基础上,运用评价指标体系对A研究所的项目管理能力进行实证分析,有效显示了其项目管理能力水平和主要不足之处。     

基于能力分析的空间对抗装备体系效能评估方法

首先研究了空间对抗的核心能力要素;然后研究了空间对抗装备体系的构成,即将核心能力要素细化为基本能力要素并映射到空间对抗装备子系统;最后构建由作战能力指标→核心能力指标及权重赋值→基本能力指标及权重赋值→单项效能指标及权重赋值组成的指标体系,并提出基于该指标体系的单项效能评价→系统综合评价→体系综合评价→作战效能评价→结果验证的综合评估途径.     

三峡库区典型滑坡危险度评价方法探讨

随着滑坡学的发展,如何定量和客观的评价典型滑坡的危险度越来越得到关注,根据典型滑坡的强度指标和发生可能性指标建立典型岩质滑坡危险度评价指标体系,利用信息熵原理,结合巫山县21个典型岩质滑坡计算各评价因子客观权重,建立定量评价模型.计算巫山县21个典型岩质滑坡的危险度,通过实地调查对评价结果进行对比验证,危险度评价结果处于高危险度的有3个点,占14.2%;中等危险度14个,占66.7%;低危险度4个,占19.1%;准确率达90.4%,此模型可作为评价典型滑坡危险度的新方法进行推广运用,为滑坡的防治提供依据.     

国际科技组织影响力评价指标体系构建及实证研究

国际科技组织影响力决定其发挥多边合作作用、实现社会使命的能力。构建国际科技组织影响力评价指标体系,有助于判断不同国际科技组织影响力的水平高低,为推动我国科研人员在具有影响力的国际科技组织任职提供参考。本研究利用文献调研法、文献计量法以及德尔菲法,从学术影响力、社会影响力、全球治理影响力三方面构建了国际科技组织影响力评价指标体系,包括3个一级指标和12个二级指标,借助德尔菲法为指标赋权,并采用客观数据对地学类19个国际科技组织进行实证分析。结果显示,本研究设计的国际科技组织影响力评价指标体系和指标量化公式较为科学合理,可操作性和实践应用价值较高,可以为促进我国科学家在国际科技组织任职、推动我国主导的国际科技组织的发展提供参考。     

矿产行业人力资源管理者胜任力评价研究

以矿产行业人力资源管理者为研究对象,就其胜任力问题展开研究,以期为矿产行业人力资源管理者能力的提升提供理论依据。在梳理国内外相关文献的基础上,编制出初始评价指标体系,随后经过2轮德尔菲法修正,构建出包含5个一级指标、由19个二级指标组成的矿产行业人力资源管理者胜任力评价指标体系,而后由专家小组16名成员赋值,运用层次分析法(AHP)确定各指标最终计分权重,权重由高至低依次为人力资源管理技能、战略性贡献、个人素质、经营知识和应变反应;最后,结合矿产行业W集团案例进行实证检验,证明了评价指标体系的可行性与可靠性。     

大件运输辅助决策系统的应用评价研究

大件运输辅助决策系统有助于提高大件运输的可靠性和安全性，为了对其实际应用效果进行评价研究，首先从目标功能、技术性能、经济效果三个方面构建了大件运输辅助决策系统的应用评价指标体系，并提出基于灰色关联度的评价指标权重确定方法，然后采用灰色统计方法建立测评矩阵，运用模糊综合评价法对辅助决策系统的应用效果进行评价。最后，通过实例验证论文提出的评价体系的有效性和可行性。     

交通运输可持续发展体系的评估方法初探

可持续发展是当今交通运输理论的研究热点，本文构造和分析了交通运输可持续发展的理论及其特点，在此基础上提出了一个评价指标体系。最后引入基于重心的模糊综合评判理论对该指标体系进行评价。     

基于 R-RNN的孵化器运营水平评价及应用

针对科技企业孵化器运营水平难以科学定量评估的问题,提出了基于粗糙集和 RBF神经网络的 R RNN孵化器运营水平评价模型.基于孵化器运营工作原理的归纳分析,提出多层次孵化器运营水平评价指标体系.根据指标重要程度采用粗糙集理论对评价指标进行预处理,去除冗余指标项,选取重要控制指标并减少网络输入维度,进而采用 RBF神经网络对科技企业运营水平进行综合评价.最后通过具体的应用实例验证了该评价模型的有效性与可行性     

城市交通环境可持续发展指标体系的建立及评价

以城市交通环境的可持续发展为出发点，建立了上海市可持续交通指标体系.采用Expert Choice Model（ECM）模型，以层次分析法为基本原理，对各类指标进行权重的计算;利用隶属函数及线性加权法进行综合指数的计算，从而对上海市城市交通可持续发展状况进行评价。     

Forecasting Private Consumption by Consumer Surveys

Survey‐based indicators are widely seen as leading indicators for economic activity. As such, consumer confidence might be informative for the future path of private consumption. Although the indicators receive high attention in the media, their forecasting power often appears to be very limited. This paper takes a fresh look at the data that serve as a basis for the consumer confidence indicator (CCI) reported by the EU Commission for the euro area. Different pooling methods are applied to exploit the survey information. Forecasts are based on mixed data sampling (MIDAS) and bridge equations. While the CCI does not outperform the autoregressive benchmark, the new indicators are able to raise forecasting performance. The best performing indicator should be built upon pre‐selection methods. Data‐driven aggregation methods should be preferred to determine the weights of the individual ingredients. Copyright © 2011 John Wiley & Sons, Ltd.     

Mixed-frequency forecasting of crude oil volatility based on the information content of global economic conditions

This paper subjects six alternative indicators of global economic activity to empirically examine their relative predictive powers in the forecast of crude oil market volatility. GARCH-MIDAS approach is constructed to accommodate all the relevant series at their available data frequencies, thereby circumventing information loss and any associated bias. We find evidence in support of global economic activity as a good predictor of energy market volatility. Our forecast evaluation of the various indicators places a higher weight on the newly developed indicator of global economic activity which is based on a set of 16 variables covering multiple dimensions of the global economy, whereas other indicators do not seem to capture. Furthermore, we find that accounting for any inherent asymmetry in the global economic activity proxies improves the forecast accuracy of the GARCH-MIDAS-X model for oil volatility. The results leading to these conclusions are robust to multiple forecast horizons and consistent across alternative energy sources.     

Quarterly forecasts of the italian business cycle by means of monthly economic indicators

Recent years have witnessed a growing availability of high-frequency indicators which can be used to forecast future economic activity. This paper shows how some of the widely known monthly economic indicators at present available in Italy can be used in a systematic and coordinated manner to forecast the main variables of the National Accounts. In order to reduce as much as possible the amount of judgment in the analysis of the business cycle, a model-based approach is adopted. Thus, a pseudo macro-econometric model of the Italian economy is built, which can be used to produce forecasts one semester ahead of the last National Accounts data release. The model can be used autonomously as well as in combination with the Bank of Italy's quarterly econometric model.     

无线传感器网络中OOFSK和FSK能耗性能

无线传感器网络（WSNs）节点通常使用电池来供电,这成为限制其广泛应用的瓶颈．所以低功耗WSNs的设计成为人们研究的重点．WSNs的传输体制很大程度上决定了整个网络的能耗性能．本文中将频移键控调制（FSK）和开关频移键控调制（OOFSK）两种高效的传输方式引入WSNs,通过建立基本通信模型,推导他们的能耗性能指标及变化趋势．通过数值分析结果可知,在低信噪比、低OOFSK调制占空比等条件下,OOFSK传输具有明显的能耗优势．同时进一步分析得到OOFSK和FSK调制在WSNs中的应用场景,对低功耗WSNs的调制模式设计具有积极作用．     

Assessment of agricultural energy consumption of Turkey by MLR and Bayesian optimized SVR and GPR models

Agricultural productivity highly depends on the cost of energy required for cultivation. Thus prior knowledge of energy consumption is an important step for energy planning and policy development in agriculture. The aim of the present study is to evaluate the application potential of multiple linear regression (MLR) and machine learning tools such as support vector regression (SVR) and Gaussian process regression (GPR) to forecast the agricultural energy consumption of Turkey. In the development of the models, widespread indicators such as agricultural value-added, total arable land, gross domestic product share of agriculture, and population data were used as input parameters. Twenty-eight-year historical data from 1990 to 2017 were utilized for the training and testing stages of the models. A Bayesian optimization method was applied to improve the prediction capability of SVR and GPR models. The performance of the models was measured by various statistical tools. The results indicated that the Bayesian optimized GPR (BGPR) model with exponential kernel function showed a superior prediction capability over MLR and Bayesian optimized SVR model. The root mean square error, mean absolute deviation, mean absolute percentage error, and coefficient of determination (R²) values for the BGPR model were determined as 0.0022, 0.0005, 0.2041, and 0.9999 in the training phase and 0.0452, 0.0310, 7.7152, and 0.9677 in the testing phase, respectively. As a result, it can be concluded that the proposed BGPR model is an efficient technique and has the potential to predict agricultural energy consumption with high accuracy.     

基于响应面法的汽车操纵稳定性多目标优化

利用ADMS／CAR软件建立整车的虚拟样机模型,对其进行转向盘转角阶跃试验和蛇形试验,井根据相关评价计分标准,得到整车模型在这两种试验中的评价计分值。然后以客观定量评价指标为目标函数,利用ADAMS／Insight及Matlab软件结合响应面法对整车的操纵稳定性进行多目标综合优化,优化后的评价计分值明显提高,表明此方法可以用于汽车操纵稳定性的多目标优化。     

The leading indicator approach to economic forecasting—retrospect and prospect

Our purpose in this paper is to explain briefly the theory and rationale underlying the leading, coincident and lagging indicators, describe the more important statistical procedures used, and review the evidence on how the indicators have performed in practice. The tests of performance concentrate on data not used in the selection of the indicators, in the United States and nine other countries. We conclude with some suggestions for future research and development, including the application of the approach to the analysis of inflation.     

风能技术发展中的几个问题

改善能源结构，利用可再生能源，减轻环境污染，提高人民生活质量，已成了全球能源工业关注的一个热点，风能是目前最有开发利用前景和技术最成熟的一种新能源和可再生能源之一。随着风能开发和利用的发展，风能技术也取得了显著的进步，并逐渐成为能源技术中的一个分支。本文简要介绍当前风能技术发展中的几个关注的问题。     

Forecasting inflation using economic indicators: the case of France

In order to provide short‐run forecasts of headline and core HICP inflation for France, we assess the forecasting performance of a large set of economic indicators, individually and jointly, as well as using dynamic factor models. We run out‐of‐sample forecasts implementing the Stock and Watson (1999) methodology. We find that, according to usual statistical criteria, the combination of several indicators—in particular those derived from surveys—provides better results than factor models, even after pre‐selection of the variables included in the panel. However, factors included in VAR models exhibit more stable forecasting performance over time. Results for the HICP excluding unprocessed food and energy are very encouraging. Moreover, we show that the aggregation of forecasts on subcomponents exhibits the best performance for projecting total inflation and that it is robust to data snooping. Copyright © 2007 John Wiley & Sons, Ltd.     

Conformational coupling between structural units. A decisive step in the functional structure formation]

Proteins built up of several structural domains are compared with oligomeric proteins made up of several subunits. On this basis the functional consequences of a conformational coupling between domains are analyzed. From the data obtained on the elastase molecule it is proposed that the last step in protein folding insures the optimal coupling between domains and the energy of interaction is utilized for catalysis.