Effect of Merging of the Convective Cloud Clusters on Occurrence of Heavy Rainfall

Sun et al., (1983) have given some favourable environmental conditions and have shown that there are four common features in convective rainstorms. In this paper, an important process of evolution of cloud systems was revealed when heavy rainfall occurred based on the diagnostic analysis of heavy rainfall cases. When the different cloud systems merge into a large one, the mesoscale heavy rainfall occurs and enhances. In other words, the process of evolution of cloud systems emphasized in this paper is the process of interaction between two cloud systems when the heavy rainfall occurs. The favourable environmental condition is also investigated.

A COMPREHENSIVE ANALYSIS OF INTERACTIONS BETWEEN MESO-SCALE CONVECTIVE CLOUD CLUSTERS IN TYPHOONS AND MESOSCALE HEAVY RAINS

In this paper, time and space distribution regularity of meso-scale heavy rains in five selected typhoons which landed at Fujian from 1996 to 1998 has been analyzed. Besides, with hourly digitized satellite infrared imagery, the features of the mesoscale are revealed for the genesis and evolution of mesoscale convective systems in typhoons. It indicates that the intensity of mesoscale storms is closely connected with the temperature and the area of the coldest cloud cluster. The heavy rainfall usually emerges on the eastern side of the mesoscale convective cloud clusters, where the cloud mass is developing and with a dense gradient and big curvature of isoline of the cloud top temperature.

Dynamic Trigger and Moisture Source of Two Typical Meiyu Front Rainstorms Associated with Eastward-Moving Cloud Clusters from the Tibetan Plateau

Eastward-moving cloud clusters from the Tibetan Plateau(TP)often trigger heavy rainfall events in the Yangtze River basin in summer.Forecasting these events in an operational environment remains a challenging task.Here,dynamical diagnosis and a Lagrangian trajectory model are used to analyze the background atmospheric circulation,maintenance mechanism,and moisture transport of two Meiyu front rainstorms(MYFR)during 30 June-2 July 2016 and 17-19 June 2018 associated with eastward-moving cloud clusters from the TP.It is shown that in both cases heavy rainfall is characterized by semi-continuous rainbelts extending from the eastern TP to the Yangtze River valleys with eastward-spreading convective clouds weakening and strengthening alternately from the eastern TP to downstream regions.Following the track of positive water vapor advection,centers of positive vorticity propagate downstream through the Sichuan basin.The baroclinic thermodynamic–dynamical interaction and the barotropic nonequilibrium force work against each other in the development of the MYFR.Specifically,during the early stage of precipitation development,the barotropic non-equilibrium force dominates,while during the period of heavy precipitation the baroclinic thermodynamic-dynamical interaction dominates.The convergence associated with the baroclinic thermodynamic-dynamical interaction guarantees the persistence of heavy precipitation.Compared to the climate mean state(1988-2018),both MYFR events associated with eastward-moving cloud clusters from the eastern TP are characterized by increased moisture transport from the southwest.One of the major paths of moisture transport in both cases is along the south side of the TP,directly connected to the eastward movement of cloud clusters.

Energy Optimization Oriented Three-Way Clustering Algorithm for Cloud Tasks

Cloud computing has developed as an important information technology paradigm which can provide on-demand services. Meanwhile,its energy consumption problem has attracted a grow-ing attention both from academic and industrial communities. In this paper,from the perspective of cloud tasks,the relationship between cloud tasks and cloud platform energy consumption is established and analyzed on the basis of the multidimensional attributes of cloud tasks. Furthermore,a three-way clustering algorithm of cloud tasks is proposed for saving energy. In the algorithm,f irst,t he cloud tasks are classified into three categories according to the content properties of the cloud tasks and resources respectively. Next,cloud tasks and cloud resources are clustered according to their computation characteristics（ e. g. computation-intensive,data-intensive）. Subsequently,greedy scheduling is performed. The simulation results showthat the proposed algorithm can significantly reduce the energy cost and improve resources utilization,compared with the general greedy scheduling algorithm.

Road Surface Modeling and Representation from Point Cloud Based on Fuzzy Clustering

为从吵闹的点云当模特儿的自动道路表面的一个计划被介绍。点云的正常向量被本地飞机的距离加权的适合估计。然后，从噪音的道路表面的自动识别基于正常向量，平均值与是计算的模糊聚类被执行，点云的投射飞机被创造因此获得几何模型。基于归因各指的紧张的模糊聚类，道路表面上的不同目标为代表丰富的外观被分配不同颜色。这个无指导的方法在重建并且显示更好的道路表面在实验和表演伟人有效性被表明。

基于多线激光雷达的井下斜坡道无人矿卡定位与建图方法

井下斜坡道的定位与建图是实现井下斜坡道无人驾驶的关键技术之一,矿山井下斜坡道区域为典型非结构化环境特征,且道路具有一定倾斜角度,采用传统SLAM算法无法获得精确里程计信息,导致定位与建图精度难以满足无人矿卡行驶需求。针对上述问题,通过研究激光SLAM(Simultaneous Localization And Mapping)算法LeGO-LOAM,笔者提出一种适用于矿山井下斜坡道环境的定位与建图方法。首先,针对井下斜坡道口两侧均为光滑水泥墙壁,特征点稀少问题,设计了基于人工路标的辅助增强定位方法,有效增加点云特征数量,从而优化位姿估计结果,避免建图漂移现象;然后在特征预处理阶段,提出了一种基于激光点云高度差与坡度信息融合的提取地面点高效算法,通过改善地面地点的选取策略,针对倾斜坑洼路面仍能有效识别地面点,解决了井下斜坡道定位与建图倾斜角度大、误差大等问题;其次,基于CVC(Curved-Voxel Clustering)聚类算法设计了一种斜坡道点云曲率体素聚类算法,采用曲率体素和基于哈希的数据结构对点云进行分割,大幅提高在井下稀疏、噪声环境下点云聚类的鲁棒性;最后,运用Scan-To-Map进行点云匹配,同时兼顾点云配准的性能与速度。在中钢集团山东某井下斜坡道的现场实验证明:与原算法相比精度提升13.15%,Z轴误差降低22.3%,地图质量明显提升,能有效解决井下无人驾驶建图及定位的难题。

基于反射强度的改进欧式距离聚类钢轨点云分割方法

线路点云数据结构化是深化专业计算与分析的技术前提。点云分割是点云数据结构化的基础。钢轨作为轮轨走行面,其空间位置的连续及平顺情况直接影响行车安全,因此轨道结构分割中,首先需对钢轨进行分割处理。针对传统欧式距离聚类中线路全景点云数据遍历导致距离阈值难统一、难界定,造成分类过多不易查找,或人工选取初始点及调参带来的自动化程度不高的情况,提出基于反射强度的改进欧式距离聚类钢轨点云分割方法。在对轨道结构特性分析的基础上,采用布料滤波算法进行地面滤波,区分地面点与地物点,精简线路点云为轨道结构点云;融合点云反射强度属性,提出提取率概念,确定钢轨高反射强度区间,进行钢轨顶面点云预分割,进而以轨顶面预分割点作为初始点,根据钢轨断面轨头高和轨头宽构造对角线长度来计算距离阈值,由Kd-Tree找到小于轨头距离阈值的点进行欧式距离聚类,实现对轨头凸集点云的分割。多路段钢轨点云分割试验,精确率及召回率均大于90%,说明该方法可行有效。

基于激光点云的橡胶树参数反演与数字孪生构建

基于激光雷达(Light Detection And Ranging,LiDAR)数据重建树体三维模型并精准获取林木空间枝干结构参数对林木性状评价、森林动态经营管理与可视化研究具有重要意义。为此提出一种基于骨架细化提取的树木模型重建方法。首先,采用FocusS350/350 PLUS三维激光扫描仪获取3块不同树龄橡胶树的样地数据。然后,作为细化建模的重点,将枝干点云从原始树点中分离出来,再将其过度分割为若干点云簇,通过相邻点云簇判断是否有分枝以及动态确定骨架点间距,并将其运用在空间殖民算法以此来生成树的三维骨架点和骨架点连通性链表,根据连通链表结构自动识别树木中的主枝干和各个一级分枝,再通过广义圆柱体生成树干完成树木三维重建。最后,利用数字孪生技术对这3块不同树龄样地树木进行三维实景建模,使其穿越时空在同一空间中重现,以便更为直观地观察树木在生长过程中的形态变化。该算法得到的橡胶树胸径与实测值比对为,决定系数(R^(2))>0.91,均方根误差(root mean square Error,RMSE)<1.00 cm;主枝干与一级枝干的分枝角为,R^(2)>0.91,RMSE<2.93;一级枝干直径为,R^(2)>0.90,RMSE<1.41 cm;将3个树龄放在一起计算其生长参数,并与实测值进行对比,发现该算法同样适用于异龄林样地的各个生长参数计算。同时发现橡胶树的一级枝条的直径越大,其相对应的叶团簇体积就越大。运用人工智能的理论模型来处理林木的激光点云数据,旨在为森林的可视化以及树木骨架结构的智能化分析与处理等研究领域提供有价值的参考。

一种基于目标点云分布特性的动态聚类算法

激光雷达在自动驾驶系统的目标检测任务中发挥着重要作用,但其扫描机理会使得点云分布不均匀,常规聚类算法由于参数固定会导致较多的错误聚类。为解决该问题,该文以椭圆形状作为邻域空间,设计基于采样点位置的邻域自适应调整策略,提出一种基于目标点云分布特性的动态聚类算法。通过正确聚类、过聚类等综合结果评估算法的性能,在KITTI数据集上进行了数值分析得到算法参数,并在校园环境中进行了实车对比实验。结果表明:所提算法能减少基于密度的噪声应用空间聚类(DBSCAN)中固定邻域所造成的70.60%过聚类、49.76%欠聚类等错误结果,从而有效提高算法的综合聚类性能。

基于视觉图像与激光点云融合的交通标志快速识别方法

交通标志对车辆交通起到重要作用和意义,而智能交通中交通标志识别由于标志特征提取效果差,导致识别率低、识别时间长,因此,提出一种新的基于视觉图像与激光点云融合的交通标志快速识别方法。采用双边滤波方法预处理原始激光点云数据;通过归一化处理得到视觉图像激光点云融合的目标空间激光点云位置测距数值;通过测距值获取目标图像位置,归一化处理交通标志视觉图像,引入k均值聚类算法二聚类处理图像,采用制作的切割模板切割图像感兴趣区域,提取交通标志图像的深度特征,结合卷积神经网络二次过滤特征,重新标定二次过滤后的特征,最终利用卷积神经网络模型实现交通标志快速识别;经实验对比证明,采用所提方法提取各个类型交通标志特征的提取效果较好,并且识别率达到89.74%,识别时间仅为13.1 s,干扰下识别时间最高仅为15.1 s,验证了该方法可以快速且准确识别各个类型的交通标志。

GENERATION AND DEVELOPMENT OF MESOSCALE CLOUD ON HEAVY RAIN BELT ON THE PERIPHERY OF TYPHOON 9608 (Herb)

Typhoon-induced heavy rains are mostly studied from the viewpoint of upper-level westerly troughs. It is worthwhile to probe into a case where the rain is caused by tropical cyclone system, which is much heavier. During August 3 ~ 5, 1996, an unusually heavy rainstorm happened in the southwest of Hebei province. It was caused by 3 mesoscale convective cloud clusters on the periphery of a tropical cyclone other than the direct effects of a westerly trough. Generating in a weak baroclinic environment that is unstable with high energy, the cloud clusters were triggered off for development by unstable ageostrophic gravity waves in the low-level southeast jet stream on the periphery of the typhoon. There was a vertical circulation cell with horizontal scale close to 1000 km between the rainstorm area and westerly trough in northeast China. As shown in a computation of the Q vector of frontogenesis function, the circulation cell forms a mechanism of transforming energy between the area of interest and the westerly trough system farther away in northeast China. Study of water vapor chart indicates that high-latitude troughs in the northeast portion of the rain migrate to the southeast to enhance anti-cyclonic divergence in upper-level convection over the area of heavy rain and cause rain clusters, short-lived otherwise, to develop vigorously. It is acting as an amplifier in this case of unusually strong process of rain.

基于Cloude-Pottier目标分解和聚合的层次聚类算法的全极化SAR数据的非监督分类算法研究

本文提出了一种新的基于Cloude-Pottier分解和聚合的层次聚类的全极化SAR(Synthetic Aperture Radar)数据的非监督分类算法.作者使用极化总功率SPAN来改进常规的初始化方法,并采用聚合的层次聚类算法对初始化结果进行类的合并,提高非监督分类器的性能.实验表明,该算法能获得有效的分类中心,分类结果明显优于常规的WishartH/α/A分类算法.

ECluster:一种面向数据密集计算的弹性集群

提出一种面向数据密集计算的弹性集群ECluster,并以Web Cache服务为例,研究弹性集群的性能指标和资源调度策略.弹性集群将云计算提供的可按需获取的资源与数据密集计算系统中的本地资源结合使用,当本地资源不足时获取云计算资源,动态调整数据密集计算系统中的资源供给.实验结果表明,与传统数据密集计算系统相比较,弹性集群能够有效保证数据密集计算系统的系统性能和资源利用效率.

虚拟主机云存储系统VCloudStorage及文件传输协议VCFTP

对于广域网下的文件传输和管理,云存储系统提供Web Service API、基于文件的API、基于Block的API和其他的API,通常需要在客户端安装特定程序调用这些API实现云存储功能,测试发现如果多人同时访问,传输文件失败率较高。设计了基于Web Service、HTTP和Flash技术的文件传输协议VCFTP,开发了基于虚拟主机集群的云存储系统VCloudStorage。首先建立SaaS服务模型,利用HTTP数据流存储技术,建立虚拟主机存储接口;接着建立虚拟主机传输能力、存储能力和价格能力数学模型,结合用户的传输请求建立文件传输整数规划数学模型及最优化算法,最终以此为基础设计了文件传输控制协议VCFTP。VCFTP利用Flash跨平台和富客户端技术特点,无需在客户端部署其他程序;授权的用户根据传输请求、存储要求、服务水平和当前虚拟主机状态等条件,以传输能力最优化的方式进行文件传输。实验结果表明VCFTP具有较高的性能和稳定性,VCloudStorage总吞吐量、平均传输率和文件传输成功率均优于微软SkyDrive存储、腾讯QQ邮箱存储和单虚拟主机存储。本文提出的VCFTP增强了文件传输性能和稳定性,是提高广域网网络存储系统性能的一条有效途径。

模糊熵与灰云模型在既有玻璃幕墙安全评价中的应用

针对既有玻璃幕墙的安全评价问题,考虑指标信息的不确定性与等级归属的复杂性,提出一种基于模糊熵与灰云聚类模型的既有玻璃幕墙安全评价方法。首先,以实际工程为背景,通过识别既有玻璃幕墙安全风险因素,构建一套定性与定量指标相结合的安全评价指标体系;其次,基于可变模糊云与正态云模型进行评价指标的赋值;再次,运用极差最大化组合赋权法,计算评价指标的权重;最后,引入灰云聚类模型与模糊熵,实现既有玻璃幕墙安全状态的二维评估。实例结果显示:该方法既能对玻璃幕墙的安全状态进行诊断,还能运用模糊熵,从复杂性的层面揭示既有幕墙的健康状况,进而为既有玻璃幕墙的安全评估提供可行思路。

基于密度与局部统计的单光子点云去噪方法

针对北京遥测技术研究所自主研发的64通道机载单光子激光雷达,提出一种基于密度与局部统计的二维剖面点云去噪方法:在确定信号点云的高程区间后,先使用基于密度的改进空间聚类算法粗去噪,然后使用基于局部统计的统计移除离群点算法精去噪,获取信号点云。实验结果表明,本方法可适用于多种地物类型点云,高程均方根误差为0.27 m,准确率90.78%,精度高于常规点云去噪算法,满足国产机载单光子激光雷达获取高精度地表三维轮廓的技术需求。

倾斜地面3D点云快速分割算法

依赖于平面拟合或局部几何特征区分地面障碍物的方法广泛应用于自动驾驶领域,但是在具有倾斜地形或稀疏数据的情况下,性能会降低。在倾斜地形场景中,利用激光雷达(LiDAR)提供的点云数据,通过地面点云的3D投影与直线拟合,利用栅格地图方法降低计算复杂度,实现地面点云的分割。针对非地面的点云集合,利用SLR聚类算法处理,通过设定强度特征阈值在垂直方向区分地面点与非地面点,并对扫描到的障碍物地面分类。通过实验分析,提出的算法较其他地面点云分割算法,一方面在倾斜地形上具有更好的建图效果,另一方面SLR聚类算法处理后的强度特征在X、Y、Z三个方向覆盖范围更精确,如在X方向相较于快速地面分割算法平均提高了44.0%,相较于添加了栅格地图的算法平均提高了40.1%。

改进高斯云模型及其在装备保障体系能力评估中的应用

针对云模型在评估方法使用过程容易出现雾化特性差、评估结果不能直接使用的问题,提出一种改进的高斯云模型。该模型针对相同指标的专家评估结果,利用相似关系矩阵对专家进行聚类并赋权,求解每类专家的评估高斯云模型,并将其与权重结合形成该评估指标的评估云模型;综合所有指标的评估云模型形成综合评估云;将综合评估云与云标尺进行比对得出评估结果。运用该方法对装备保障体系能力进行评估,并与传统云模型所得评估结果进行对比,证明了改进高斯云模型的可行性和有效性,为其在评估方法中的运用提供参考。

“云杀伤链”构建方法

针对传统“杀伤链”要素单一、抗毁性弱等问题,基于作战资源“虚拟化、服务化、共享化”的核心思想,提出“云杀伤链”作战构想及其系统架构。阐述装备建模、资源服务化、云服务聚类及柔性组织等关键技术,初步构建“云杀伤链”作战系统的技术框架;“云杀伤链”作战系统能以自协调、自适应的方式完成临机任务规划及兵力重组,更适合快节奏、高强度对抗的战场环境。结果表明,该方法可为军队提升网络化联合作战能力和敏捷精确打击能力提供参考。