基于交通轨迹数据的三维动态噪声地图

噪声信息具有空间传播和随距离衰减变化的特征,采用三维动态可视化形式表达噪声地图可以体现该特征。本文针对噪声的空间分布与强度变化提出一种噪声地图表达的方法,基于Bertin符号参量分析,以具有高度可变的方柱并配以深浅变化的颜色作为噪声符号,动态传递噪声信息。为进行多尺度地图展示,在不同地图等级下设有相应细节层次的符号尺寸和定位排列方式。噪声地图以Web端Mapbox为展示平台,基于交通噪声模型和GPS轨迹数据,对上海黄浦区某区域一时间段内的噪声情况进行模拟表达,实现噪声数据的立体动态化显示。三维动态的表达扩展了噪声数据的表现维度,多维度、多参量的立体动态符号不仅可准确刻画噪声的分布,而且从视觉观感上提高了受众的兴趣度和专注度,这为研究噪声的热点分布、传递趋势等空间规律提供了可视化参考。     

凸包插值算法的改进与实现

研究了凸包插值算法在n维欧拉空间构造Delaunay三角网的应用,提出了其三角剖分不惟一的重大缺陷,采用了限制区域生长法解决了这一缺陷。     

人工神经网络在云南5月雨量预测中的应用

提出了一个基于３层ＰＢ神经网络的云南５月雨量的短期气候预测模型。由于神经网络本身是一个非线性动态系统,将其应用到短期气候变化预测这一非线性系统中,更能反映出气候系统状态量之间的物理关系和动力行为特性。并用该预测模型对云南５个区域１９９１～１９９８年的５月雨量距平趋势进行了共４０次的预测试验和检验,其预测的距平符号相关准确率可达到７７．５％。     

基于无尺度结构的苏南乡镇公路网分析

从图论视角建立区域尺度乡镇公路网络图,并基于节点度D提出等级节点度D_r及规模节点度D_p。从无尺度结构视角,运用D、D_r、D_p指数及数理统计方法描述苏南乡镇公路网的异质结构,结果表明苏南乡镇公路网D并非无尺度结构,但其D_r和D_p符合无尺度结构。利用SPSS相关分析和GIS空间分析发现D_p与D相关性小,但与D_r相关性高且空间对应明显。乡镇D_p-D_r的互动机制空间显示为"核-带"式区域乡镇发展模式,这种开敞组团格局有利于区域发展与保护双赢,由此建议苏州、无锡和常武地区控制乡镇密集分布,集中合并乡镇,适当限制高级公路发展;南京、镇江及金坛、溧阳地区加强高级公路地"带"乡镇的发展力度。     

地图数据缩编更新的模式分类与选择

地图数据缩编更新模式是缩编更新技术流程设计及软件模块开发的基础。根据缩编和更新对象的不同归纳了缩编更新的4种模式,结合当前地图自动综合理论技术水平与数据组织管理现状,认为现阶段最合理的模式为新旧数据叠加缩编更新模式。基于该模式分析道路数据缩编更新的技术流程并开发了相应的软件模块,应用于国家1∶5万地理信息系统中道路数据的更新,从而验证了该模式的可行性。     

Engineering characteristics and uses of duricrusts in Australia

The uses and shortcomings of duricrusts (ferricrete, calcrete and silcrete) in engineering construction (as used for road‐base, aggregate, foundation materials and aquifers) are reviewed. Australian production of these materials represents about one‐third of all unprocessed road‐base and they are especially important as pavement courses for lightly trafficked, low‐cost rural and outback roads. However, duricrusts are regarded as marginal materials at best because of their typically poor grading, particle unsoundness, high fines plasticity, and absorption of water and bitumen. These materials are used because they are available locally in areas that are otherwise lacking in hard rock materials, such as deeply weathered and sedimentary rock terrains. The weathering profiles of which they form part are characterized by high permeability (despite being clay‐rich), variable cementation, low compressibility and a tendency to become weaker with depth. Although the more indurated layers are unrippable, they are also difficult to blast. Pedogenic (nodular) duricrusts were formerly sought for natural road‐base, because they occur widely and require only rudimentary processing. However, well‐cemented groundwater (vadose) duricrusts are now the preferred deposits, even though they require crushing and screening. Ferricrete is the most widely exploited of the duricrusts for engineering purposes, especially in northern and southwestern Australia, although calcrete is important in South Australia and in the Murray Basin. Silcrete is only a minor source of aggregate and road‐base, mainly in western Queensland.     

Are artificial neural network techniques relevant for the estimation of longitudinal dispersion coefficient in rivers? / Les techniques de réseaux de neurones artificiels sont-elles pertinentes pour estimer le coefficient de dispersion longitudinale en rivières?

Abstract

Abstract Accurate application of the longitudinal dispersion model requires that specially designed experimental studies are performed in the river reach under consideration. Such studies are usually very expensive, so in order to quantify the longitudinal dispersion coefficient, as an alternative approach, various researchers have proposed numerous empirical formulae based on hydraulic and morphometric characteristics. The results are presented of the application of artificial neural networks as a parameter estimation technique. Five different cases were considered with the network trained for different arrangements of input nodes, such as channel depth, channel width, cross-sectionally averaged water velocity, shear velocity and sinuosity index. In the case where the sinuosity index is included as an input node, the results turned out to be better than those presented by other authors.     

Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers

Abstract

The study of sediment load is important for its implications to the environment and water resources engineering. Four models were considered in the study of suspended sediment concentration prediction: artificial neural networks (ANNs), neuro-fuzzy model (NF), conjunction of wavelet analysis and neuro-fuzzy (WNF) model, and the conventional sediment rating curve (SRC) method. Using data from a US Geological Survey gauging station, the suspended sediment concentration predicted by the WNF model was in satisfactory agreement with the measured data. Also the proposed WNF model generated reasonable predictions for the extreme values. The cumulative suspended sediment load estimated by this model was much higher than that predicted by the other models, and is close to the observed data. However, in the current modelling, the ANN, NF and SRC models underestimated sediment load. The WNF model was successful in reproducing the hysteresis phenomenon, but the SRC method was not able to model this behaviour. In general, the results showed that the NF model performed better than the ANN and SRC models.

Citation Mirbagheri, S. A., Nourani, V., Rajaee, T. & Alikhani, A. (2010) Neuro-fuzzy models employing wavelet analysis for suspended sediment concentration prediction in rivers. Hydrol. Sci. J. 55(7), 1175–1189.     

Knowledge integration in sustainability governance through science-based actor networks

Understanding how science, technology and innovation can best help to accelerate progress in achieving sustainable development remains a grand challenge for researchers and practitioners. In the context of the global consultation process for preparing a post-2015 Sustainable Development Agenda, various science-based actor networks have emerged, aiming to translate research into political decision-making and to inform transformations towards sustainability. Over the last years, these networks seem to have taken an ever-growing role in structuring the science-policy interface in global sustainability governance. The question arises, however, how they understand and organize ‘scientific knowledge integration’ in sustainability politics.This study offers a structured comparison of twelve global science-based actor networks engaged in the implementation of the Sustainable Development Goals. It shows that these networks use two types of strategies to foster scientific knowledge integration in sustainability governance. A new framework emerges, in which each strategy corresponds to two main approaches of scientific knowledge integration: The entrepreneurial strategy generally seeks to advance advice-oriented and solution-oriented knowledge processes, while assessment-oriented and learning-oriented processes in scientific knowledge integration are mainly promoted through a mediating strategy.     

Asymptotic Rayleigh instantaneous unit hydrograph

The instantaneous unit hydrograph for a channel network under general linear routing and conditioned on the network magnitude,N, tends asymptotically, asN grows large, to a Rayleigh probability density function. This behavior is identical to that of the width function of the network, and is proven under the assumption that the network link configuration is topologically random and the link hydraulic and geometric properties are independent and identically distributed random variables. The asymptotic distribution depends only on a scale factor, , where is a mean link wave travel time.