中国城市化与能源强度关系的交互动态响应分析

基于1990-2009年的统计数据,建立城市化率和能源强度间的向量自回归模型,运用协整分析、脉冲响应函数和动态方差分解法,从不同视角对两组变量的交互动态响应关系进行分析和预测,旨在揭示我国城市化水平与能源利用效率的内在联系、互动机制与发展趋势。分析结果表明:尽管在短期内呈现波动态势,我国城市化水平与能源强度之间存在长期均衡关系;两组变量的动态脉冲响应为负,体现出城市化率和能源强度之间的反向变动走势;与城市化相比,能源强度的脉冲曲线波动剧烈,说明单纯依靠能源系统内部来改善能源效率缺乏可持续性;方差分解时序值显示,能源强度对城市化变动因素的累计贡献较低,而城市化水平对能源强度变动的影响显著且增长迅速,说明能源强度的降低并不是城市化率提高的主要动力,反之城市化水平的提高对能源强度的下降具有较强的促进作用。由此可见,通过城市的优化开发与系统建设,能够有效促进能源的可持续利用,实现能源消费与经济增长间的均衡发展。     

Low-carbon transition of iron and steel industry in China: Carbon intensity, economic growth and policy intervention

As the biggest iron and steel producer in the world and one of the highest CO₂ emission sectors, China's iron and steel industry is undergoing a low-carbon transition accompanied by remarkable technological progress and investment adjustment, in response to the macroeconomic climate and policy intervention. Many drivers of the CO₂ emissions of the iron and steel industry have been explored, but the relationships between CO₂ abatement, investment and technological expenditure, and their connections with the economic growth and governmental policies in China, have not been conjointly and empirically examined. We proposed a concise conceptual model and an econometric model to investigate this crucial question. The results of regression, Granger causality test and impulse response analysis indicated that technological expenditure can significantly reduce CO₂ emissions, and that investment expansion showed a negative impact on CO₂ emission reduction. It was also argued with empirical evidence that a good economic situation favored CO₂ abatement in China's iron and steel industry, while achieving CO₂ emission reduction in this industrial sector did not necessarily threaten economic growth. This shed light on the dispute over balancing emission cutting and economic growth. Regarding the policy aspects, the year 2000 was found to be an important turning point for policy evolution and the development of the iron and steel industry in China. The subsequent command and control policies had a significant, positive effect on CO₂ abatement.     

Causasilty among wildfire,ENSO, timber harvest,and urban sprawl: The vector autoregression approach

This article demonstrates the applicability of vector autoregression (VAR) modeling in probing the causality relationships among wildfire, El Niño/Southern Oscillation (ENSO), timber harvest, and urban sprawl in the U.S. The VAR approach allows for the multi-directional, multi-faceted interactions among the variables concerned and enables us to portray the temporal impacts of ENSO, the volume of timber harvested, and urban sprawl on wildfire. The empirical analysis, though intended mainly for illustration, reveals that an individual factor may not affect wildfire activity (number of fires and area burned) when acting alone, but can significantly influence fire activity when coupled with other factors, and that wildfire activity has feedback effects on other variables. The impact of a change in ENSO, the volume of timber harvested, and urban population density on wildfire activity could last two decades with the most noticeable impact occurring in the initial 5–10 years. Though ENSO, timber harvest, and urban sprawl all Granger-cause wildfire activity, the impulse response functions show that wildfire activity is more responsive to urban population density than to the volume of timber harvested or ENSO. Thus, controlling urban sprawl represents another option for wildfire mitigation; and integrative wildfire management is essential.     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

基于SVR的船舶溢油事故预测

船舶溢油事故的预测,是确定所需应急资源多少的重要依据;但船舶溢油事故具有小样本性,传统预测方法不再适用。针对船舶溢油事故的小样本性,该文选择SVR模型对其进行预测;SVR算法的关键是核函数的选择及自由参数的确定,针对上述问题该文分别采用交叉验证法、遗传算法;并在matlab软件上建立SVR模型,最后将该模型应用于上海港水域船舶溢油事故的预测。     

珠江片水环境承载力评价研究

以珠江片水域为研究对象,在梳理国内外相关文献的基础上,针对珠江片现有水资源环境与社会发展关系情况,构建了珠江片水环境承载力评价指标体系,而后采用变异系数法客观确定指标权重,再运用向量模法对珠江片水环境承载力进行评价,揭示并分析了近年珠江片水环境承载力的变化趋势。结果表明,2006~2014年间珠江片水环境承载力呈缓慢持续上升趋势,承载力水平值介于0.04~0.06之间,说明珠江片水环境承载力仍处于较低水平。     

移动Ad hoc网络路由协议的安全性分析与对策

移动Ad hoc网络是一种自组织、多跳的无线网络,由于其独特性能使移动Adhoc网络面临着比现有网络具有更大的安全挑战,其中路由安全对该网络的安全性起着关键性的作用。在介绍移动Ad hoc网络主要路由协议及其特点的基础上,笔者深入研究了移动Ad hoc网络路由协议中存在的黑洞、拒绝服务等安全漏洞;详细分析了几种主要的Ad hoc路由协议的安全性增强方案;根据不同路由协议的特点,分别提出了利用单向散列链改进距离矢量路由协议安全性的两种方案;分析了一种用于改善源路由协议安全性的方案的可行性。最后,指出了移动Ad hoc网络路由协议安全性问题的进一步改进和研究方向。     

基于RBF和PSO的双喉道气动矢量喷管优化设计

本文探索了一种能多变量综合优化的方法,即对喷管进行参数化设计后,用均匀试验设计(UED)将试验样本均匀散布在设计区间内,求出各性能参数后,利用径向基神经网络(RBF)对试验样本进行拟合,再用粒子群算法(PSO)对训练好的神经网络进行寻优,找出了更好的双喉道气动矢量喷管设计参数组合。数值模拟结果显示,优化后的双喉道气动矢量喷管的矢量角有了明显提高。试验表明这种优化方法具有很好的优化能力,可以用来对喷管几何外形进行参数优化。      

沈阳地区一次颗粒物重污染天气过程的气象成因分析

为探究沈阳地区重污染天气成因,文章利用地面、高空气象观测资料、风廓线雷达资料、NECP再分析资料以及大气污染物监测资料,对2019年3月1～6日沈阳地区出现的一次持续性重污染天气过程,探讨了大气污染物质量浓度、地面气象要素变化特征、大气环流配置与外来输送等特征.结果表明,均压场、地面风场弱及辐合、高温高湿是本次重污染天...     

基于光谱和纹理的支持向量机矿化信息提取——以青海黄南州吉地地区为例

针对传统矿化信息提取方法单一利用光谱或纹理,信息量相对较少且需要大量样本的缺陷,利用基于光谱和纹理的支持向量机(SVM)原理,建立矿化信息提取模型。选择青海黄南州吉地地区作为典型研究区。首先提取研究区光谱和纹理信息,选取训练样本;然后求解最优超平面,进而确定决策函数;最后泛化推广识别其它待识别的样本。通过所提取的遥感蚀变异常信息与原有矿区叠加分析,叠加基本吻合;从野外实地验证来看,均发现了不同程度的矿化现象,并指出了4个重点异常区。