城市道路网络特征对交通事故作用机理的研究进展

机动交通快速发展背景下城市道路交通安全问题日益严峻,道路网络作为影响区域交通流与居民交通出行行为的关键因素,对区域交通事故的数量、类型和空间分布具有重要影响。论文从道路布局形式与几何拓扑特征2个方面归纳总结城市道路网络特征对交通事故的作用机理,并通过梳理道路网络与交通出行行为的关系分析其对交通事故的潜在影响。研究指出,格网型、平行曲线型、回路尽端型等道路网络布局形式以及中心性、连通性等道路网络拓扑指标,对交通事故的类型、频率和严重程度的影响存在差异性和空间尺度效应;合理的交叉口密度、路网密度、街区密度等道路网络几何特征对于提升交通安全水平具有重要作用。未来研究需要进一步运用复杂网络理论刻画道路网络的结构、功能等特征,在控制居住自选择效应的基础上,从交通出行行为视角深入分析复杂道路网络对交通事故的作用机制与非线性影响,同时考虑道路网络特征与建成环境的潜在交互作用。     

`Our resistance will be as transnational as capital': Convergence space and strategy in globalising resistance

This paper analyses the emerging globalising networks of communication, solidarity, and information-sharing between social movements and other resistance formations in opposition to neoliberal globalisation. In particular, the paper focuses upon People's Global Action – a network of various social movemnets and grassroots intitiatives from around the world. The paper argues that such a network represents not an organisation, but rather a convergence space – a heterogenous affinity of common ground between resistance formations wherein certain interests, goals, tactics and strategies converge. The paper analyses how space and strategy are negotiated in these globalising terrains of resistance, and argues that place-specific struggles are engaging with alliances and collaborations across diverse boundaries of gender, generation, class, and ethnicity – globalising the common ground between different struggles. Explaining how the internet has been crucial to the development of these networks, the paper argues that the strategies of such networks can be interpreted, in part, through the Taoist text, The Art of War, especially the Taoist notions of terrain, knowing others, and form/lessness. In addition, the paper argues that convergence spaces are fragmented by important issues of language, power, and mobility.     

螺髻山北麓地下水化学特征与水质评价

为研究川西大凉山区螺髻山北麓地下水化学特征、演化机制以及评价地下水质现状,笔者系统采集研究区不同地段的15组地下水样品为研究对象。利用Gibbs图解法、离子比例系数法和基于RMSprop算法的BP神经网络评价法,探讨该地区地下水化学特征演化机制,评价地下水质现状,支持服务帮助当地合理开发和安全利用水资源。结果表明研究区水化学类型以Mg2+·Ca2+−HCO3–为主,其水化学离子的形成主要以岩土风化溶滤作用为主,由硅酸盐矿物与碳酸盐矿物共同控制,硅酸盐矿物控制更显著。结合地质背景,认为硅酸盐矿物主要来自火山碎屑岩类、花岗岩类、砂岩类和泥质岩类等岩石。利用BP神经网络对5000组地下水样本学习训练,对研究区样本进行评价,模型训练图像表明BP神经网络能很好拟合地下水样本训练集并且对测试集进行客观准确的判断。研究区地下水评价结果显示：Ⅰ类水质点占13.3%,Ⅱ类水质点占40%,Ⅲ类水质点占46.6%,整体水质较好,建议Ⅲ类水质地区普格县特尔果乡甲甲沟村、普格县特补乡白庙子需要加强地下水污染源调查以及水质保护。     

Texture classification of Mediterranean land cover

Maximum likelihood (ML) and artificial neural network (ANN) classifiers were applied to three Landsat Thematic Mapper (TM) image sub-scenes (termed urban, agricultural and semi-natural) of Cukurova, Turkey. Inputs to the classifications comprised (i) spectral data and (ii) spectral data in combination with texture measures derived on a per-pixel basis. The texture measures used were: the standard deviation and variance and statistics derived from the co-occurrence matrix and the variogram. The addition of texture measures increased classification accuracy for the urban sub-scene but decreased classification accuracy for agricultural and semi-natural sub-scenes. Classification accuracy was dependent on the nature of the spatial variation in the image sub-scene and, in particular, the relation between the frequency of spatial variation and the spatial resolution of the imagery. For Mediterranean land, texture classification applied to Landsat TM imagery may be appropriate for the classification of urban areas only.     

福建及其周边地区地震活动人工神经网络模型的构建

本文通过对福建及其周边地区地震活动人工神经网络模型的构建,研究了人工神经网络方法在基于该区域地震活动性指标的地震分析预报中的应用。选用含一个中章层的前向神经网络模型,并采用与之相适应的ＢＰ算法,以该地区１９７１～１９９７年的地震活动性资料为基础,用神经网络进行实际计算、分析和检验。结果表明：神经网络模型对福建及其周边地区地震震级的预测检验效果较好的,可以在一定精度范围内使震级预测的内符率达１００％     

VGI and crowdsourced data credibility analysis using spam email detection techniques

Volunteered geographic information (VGI) can be considered a subset of crowdsourced data (CSD) and its popularity has recently increased in a number of application areas. Disaster management is one of its key application areas in which the benefits of VGI and CSD are potentially very high. However, quality issues such as credibility, reliability and relevance are limiting many of the advantages of utilising CSD. Credibility issues arise as CSD come from a variety of heterogeneous sources including both professionals and untrained citizens. VGI and CSD are also highly unstructured and the quality and metadata are often undocumented. In the 2011 Australian floods, the general public and disaster management administrators used the Ushahidi Crowd-mapping platform to extensively communicate flood-related information including hazards, evacuations, emergency services, road closures and property damage. This study assessed the credibility of the Australian Broadcasting Corporation’s Ushahidi CrowdMap dataset using a Naïve Bayesian network approach based on models commonly used in spam email detection systems. The results of the study reveal that the spam email detection approach is potentially useful for CSD credibility detection with an accuracy of over 90% using a forced classification methodology.     

TPS测设道路填挖边线方法探讨

道路建设中,测设填挖线是经常遇到的问题,就此提出了TPS(全站仪)在任意控制点设站、测定辅助点和填挖点的放样方法。该方法的关键之处是,利用曲线要素推算各放样点的坐标,然后在道路施工现场附近选择一视野开阔的控制点安置TPS,一次性放样出全视野内的辅助点和填挖点,并连接填挖点组成填挖边线。为保证各阶削坡的精度,应注意保护各辅助点的平面位置,正确地削出最上阶平台,以控制以下各阶削坡。而以往的放样方法是抬竿法,需要在逐个横断面多次设站,用定向、量距、抬高的方法放样填挖点。这种方法的缺点是:效率低下,作业难度大,累计误差大。显然,用TPS一次设站,放样若干横断面填挖点的方法,提高了施工效率,降低了作业难度,且提高了放样点的精度。     

多源道路智能选取的本体知识推理方法EI北大核心CSCD

大数据时代道路数据来源日益增多,跨数据源的道路选取面临巨大挑战。本文针对数据语义不一致问题,提出一种基于本体知识推理的多源道路选取方法。首先,将1∶5万基本比例尺地形图道路数据作为基础案例,将四维图新导航电子地图和开放街道地图中的道路数据作为试验数据,基于stroke计算道路等级、长度、连通度、接近度、中介度特征项,提取特征项概念并构建本体;然后,从语义特征项和数值特征项两方面计算本体概念相似性,建立基础案例与试验数据间的关联关系;最后,基于本体和语义网规则语言定义本体通用、语义特征、数值特征三类选取规则,实现跨数据源道路选取的过程性知识推理。试验表明,本文方法可基于本体概念相似性度量消除语义差异,同时利用语义网规则语言进行知识推理,可实现多源道路数据向基本比例尺数据的智能选取。     

基于INCA和METRo的江苏省路面高温精细化预报

使用INCA（Integrated Nowcasting through Comprehensive Analysis）多源资料融合分析和短临外推预报系统的预报结果作为气象强迫场,驱动一路面温度理论预报模型（Model of the Environment and Temperature of Roads,METRo）,开展江苏省高速公路夏季路面高温预报试验,并使用公路沿线逐小时的路面温度观测资料对预报结果进行检验。结果表明:该预报方法能够较好地预报出高速公路沿线日最高路面温度的逐日变化趋势,以及日最高路面温度的大范围空间分布特征。平均日最高路面温度预报绝对偏差为4.1℃,平均相对偏差为10.8%。其中,日最高路面温度预报绝对偏差在5℃以内的站次占总数的64.5%,相对偏差在15%以内的站次占总数的74.6%,比常规业务预报方法分别提高了23.1%和25.3%。但该预报方法对较小的温度波动以及局地性较强的极端温度分布特征的预报技巧还需进一步提高。     

一种基于空时联合约束的相对定位方法

为了降低机动环境对传感器网络自身定位的影响,提出了一种基于空时联合约束的相对定位(STRP)方法。Monte Carlo仿真表明,相对于STF技术,STRP方法降低了环境对定位的影响,自主导航定位的精度提高了36%。