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。     

皖江区域城市能级与生态环境协调度的测度和发展趋势研究

随着城市能级的不断提高,城市生态环境问题也日益突出,二者间协调发展成为城市发展一致的追求。以皖江区域10个城市作为研究地域单元,构建了城市能级与生态环境的指标体系,并建立了城市能级与生态环境的协调度模型。在此基础上,对皖江区域2002~2011年的城市能级与生态环境协调度进行了测度,研究发现过去10a皖江区域城市能级与生态环境的协调度处于较低水平。根据测定的协调度数据,建立了协调度自回归预测模型,并运用该模型探究了未来10a皖江区域城市能级与生态环境协调度的发展趋势,结果表明皖江区域城市能级与生态环境的协调度发展水平经过拮抗期和基本协调期后不断提高,将于2019年前后趋近高质协调发展阶段,即城市能级与生态环境两个系统有序互动发展的态势。     

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.     

平原丘陵过渡带土壤有机碳空间分布及环境影响

为定量分析景观过渡带中土壤有机碳空间分布及环境影响,将环境因子纳入空间自回归模型与地理加权回归模型分析比较,并以普通最小二乘回归模型作对照.结果表明:土壤性质指标中,容重及有效铁与土壤有机碳存在极显著相关关系;地形及区位因子中,纬度、高程、坡度、粗糙度等稳定性因素与土壤有机碳存在极显著相关关系;土壤有机碳的局部集聚性多发生在核心景观过渡带;空间回归模型的拟合优度均优于普通最小二乘回归模型,估计值的空间自相关变化趋势与实测值一致,残差的空间模式显著减弱;能够灵活调整权函数与带宽的地理加权回归模型能够更好地分析土壤有机碳的空间变异.模型评价方面,GWR-1和GWR-2的残差平方和较OLS分别降低了20.717%和8.799%; SLM、SEM、GWR-1、GWR-2的AIC值较OLS分别减小了5.108、5.391、19.887和11.751.除本身存在的空间自相关外,模型中土壤性质指标及环境因子能大幅解释土壤有机碳的异质性.本研究引入辅助变量,运用空间回归模型分析了平原丘陵过渡带土壤有机碳的空间变异,可为生态恢复、环境变化指示及研究区典型柑橘区的区划提供依据.     

西安市生态文明建设评价及预测

根据生态文明的涵义和生态市建设的总体思路,提出了生态文明建设3（系统层、子系统层、单项指标层）×3（经济发展,社会进步,环境保护）评价体系,其中包括25个单项指标。对西安市1998-2007年生态文明建设进行了定量评价研究,结果表明西安市生态文明建设处于整体上升的趋势;在此基础上,应用自回归预测模型对西安市经济、社会、环境和生态文明建设发展进行了预测,为西安市全面协调发展提供参考借鉴。     

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。     

基于机器学习分类算法解析EIS数据的有机涂层性能评价方法

目的 基于机器学习分类算法快速评估有机涂层的防腐性能。方法 通过实验室加速试验模拟涂层真实的退化过程,并根据测得的电化学数据,分析不同退化阶段的等效电路元件参数。随后,采用随机抽样方法获取大量数据,用于机器学习模型训练。通过对比支持向量机(SVM)、k最近邻(k-NN)和随机森林(RF)3种不同的机器学习算法,以及多种输入特征集训练的涂层性能分类器模型的准确率,分析最适合用于涂层性能快速评估的机器学习算法和电化学特征。结果 根据不同输入特征训练的k-NN和RF模型均表现出良好的预测效果,而SVM模型的预测效果相对较差。根据不同频率范围训练的分类器模型中,在低频区表现最佳,而在高频区表现较差。结论 基于阻抗虚部、虚部+实部和阻抗模值3种输入特征训练的RF分类器模型的预测效果最准确。不同频率区间内,低频区的阻抗特征更能准确表征涂层性能。     

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.     

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。