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 i...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.展开更多
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.Her...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.展开更多
Traditional spatial clustering methods have the disadvantage of ＂hardware division＂, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a gen...Traditional spatial clustering methods have the disadvantage of ＂hardware division＂, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry. Based on infrastructures＇ classification and demarcation in Zhanjiang, a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering, the comparative study of Fuzzy C-means and a coupled analysis of residential land prices. General multi-dimensional cloud model reflects the integrated char- acteristics of spatial objects better, reveals the spatial distribution of potential information, and realizes spatial division more accurately in complex circumstances. However, due to the complexity of spatial interactions between geographical entities, the generation of cloud model is a specific and challenging task.展开更多
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 in...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.展开更多
Cloud computing allows scalability at a lower cost for data analytics in a big data environment. This paradigm considers the dimensioning of resources to process different volumes of data, minimizing the response time...Cloud computing allows scalability at a lower cost for data analytics in a big data environment. This paradigm considers the dimensioning of resources to process different volumes of data, minimizing the response time of big data. This work proposes a performance and availability evaluation of big data environments in the private cloud through a methodology and stochastic and combinatorial models considering performance metrics such as execution times, processor utilization, memory utilization, and availability. The proposed methodology considers objective activities, performance, and availability modeling to evaluate the private cloud environment. A performance model based on stochastic Petrinets is adopted to evaluate the big data environment on the private cloud. Reliability block diagram models are adopted to evaluate the availability of big environment data in the private cloud. Two case studies based on the CloudStack platform and Hadoop cluster are adopted to demonstrate the viability of the proposed methodologies and models. Case Study 1 evaluated the performance metrics of the Hadoop cluster in the private cloud, considering different service offerings, workloads, and the number of data sets. The sentiment analysis technique is used in tweets from users with symptoms of depression to generate the analyzed datasets. Case Study 2 evaluated the availability of big data environments in the private cloud.展开更多
道路点云数据的障碍物检测技术在智能交通系统和自动驾驶中至关重要.传统的基于密度的空间聚类(DensityBased Spatial Clustering of Applications with Noise,DBSCAN)算法在处理高维或不同密度区域数据时,由于距离度量低效、参数组合...道路点云数据的障碍物检测技术在智能交通系统和自动驾驶中至关重要.传统的基于密度的空间聚类(DensityBased Spatial Clustering of Applications with Noise,DBSCAN)算法在处理高维或不同密度区域数据时,由于距离度量低效、参数组合确定困难导致聚类效果欠佳,因此,提出了一种基于改进DBSCAN的道路障碍物点云聚类方法 .首先,在确定Eps领域时利用孤立核函数来改进传统的距离度量方式,提高了DBSCAN聚类对不同密度区域的适应性和准确性.其次,针对猎豹优化算法(Cheetah Optimizer,CO)在信息共享和迭代更新方面的不足,提出了一种基于及时更新机制与兼容度量策略的CO优化算法(Timely Updating Mechanisms and Compatible Metric Strategies for CO Algorithms,TCCO),通过实时更新操作确保每次迭代的优秀信息得到及时沟通共享,并在全局更新时基于非支配排序与拥挤距离优化淘汰机制,平衡全局搜索和局部开发能力,提高了收敛速度和收敛精度.最后,利用孤立度量改进Eps领域,并利用TCCO优化DBSCAN聚类,自适应确定参数,提高了聚类精度和效率.在八个UCI数据集上进行测试,仿真结果表明,提出的TCCO-DBSCAN算法与CO-DBSCAN,SSA-DBSCAN,DBSCAN,KMC方法相比,F-Measure,ARI,NMI指标均有明显提升,且聚类精度更优.通过激光雷达点云数据障碍物聚类的实验验证,证明TCCO-DBSCAN能够有效地适应点云数据密度变化,获得更好的道路障碍物聚类效果,为辅助驾驶中障碍物检测提供支持.展开更多
文摘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.
基金Supported by the National Natural Science Foundation of China (41620104009 and 41975058)Science and Technology Funds of Hubei Meteorological Bureau (2022Y25 and 2022Z02)+3 种基金Joint Open Project of Key Laboratory of Meteorological Disaster,Ministry of Education&Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science&Technology (KLME202106)in part supported by the U.S. National Science Foundation (AGS-2032532)NOAA (NA20OAR4310380)
文摘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.
基金National Natural Science Foundation of China, N0.40971102 Knowledge Innovation Project of the Chinese Academy of Sciences, No. KZCX2-YW-322 Special Grant for Postgraduates＇ Scientific Innovation and So- cial Practice in 2008
文摘Traditional spatial clustering methods have the disadvantage of ＂hardware division＂, and can not describe the physical characteristics of spatial entity effectively. In view of the above, this paper sets forth a general multi-dimensional cloud model, which describes the characteristics of spatial objects more reasonably according to the idea of non-homogeneous and non-symmetry. Based on infrastructures＇ classification and demarcation in Zhanjiang, a detailed interpretation of clustering results is made from the spatial distribution of membership degree of clustering, the comparative study of Fuzzy C-means and a coupled analysis of residential land prices. General multi-dimensional cloud model reflects the integrated char- acteristics of spatial objects better, reveals the spatial distribution of potential information, and realizes spatial division more accurately in complex circumstances. However, due to the complexity of spatial interactions between geographical entities, the generation of cloud model is a specific and challenging task.
基金Supported by the Harbin Technology Bureau Youth Talented Project(2014RFQXJ073)China Postdoctoral Fund Projects(2014M561330)
文摘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.
文摘随着算力网络中计算资源与虚拟化设备的广泛应用,在算力网络虚拟化中,针对云集群弹性伸缩策略基于阈值的响应式触发过程中存在的弹性滞后问题,提出一种基于Transformer的预测式云集群资源弹性伸缩方法(Predictive Cloud Cluster Resource Elastic Scaling Method Based on Transformer,Cloudformer).该方法利用序列分解模块将云集群数据分解为趋势项和季节项,趋势项采用双系数网络分别对输入空间预测的均值和方差进行归一化和反归一化,季节项采用融合傅里叶变换的频域自注意力模型进行预测,并在模型训练过程中使用指数移动平均模型动态调整训练损失的误差范围.实验结果表明,对比最先进的五种预测式弹性伸缩算法,本文所提出的方法在保持较低的模型训练和推理时间下,不同预测窗口单变量与多变量预测均方误差分别降低了10.07%和10.01%.
文摘Cloud computing allows scalability at a lower cost for data analytics in a big data environment. This paradigm considers the dimensioning of resources to process different volumes of data, minimizing the response time of big data. This work proposes a performance and availability evaluation of big data environments in the private cloud through a methodology and stochastic and combinatorial models considering performance metrics such as execution times, processor utilization, memory utilization, and availability. The proposed methodology considers objective activities, performance, and availability modeling to evaluate the private cloud environment. A performance model based on stochastic Petrinets is adopted to evaluate the big data environment on the private cloud. Reliability block diagram models are adopted to evaluate the availability of big environment data in the private cloud. Two case studies based on the CloudStack platform and Hadoop cluster are adopted to demonstrate the viability of the proposed methodologies and models. Case Study 1 evaluated the performance metrics of the Hadoop cluster in the private cloud, considering different service offerings, workloads, and the number of data sets. The sentiment analysis technique is used in tweets from users with symptoms of depression to generate the analyzed datasets. Case Study 2 evaluated the availability of big data environments in the private cloud.
文摘道路点云数据的障碍物检测技术在智能交通系统和自动驾驶中至关重要.传统的基于密度的空间聚类(DensityBased Spatial Clustering of Applications with Noise,DBSCAN)算法在处理高维或不同密度区域数据时,由于距离度量低效、参数组合确定困难导致聚类效果欠佳,因此,提出了一种基于改进DBSCAN的道路障碍物点云聚类方法 .首先,在确定Eps领域时利用孤立核函数来改进传统的距离度量方式,提高了DBSCAN聚类对不同密度区域的适应性和准确性.其次,针对猎豹优化算法(Cheetah Optimizer,CO)在信息共享和迭代更新方面的不足,提出了一种基于及时更新机制与兼容度量策略的CO优化算法(Timely Updating Mechanisms and Compatible Metric Strategies for CO Algorithms,TCCO),通过实时更新操作确保每次迭代的优秀信息得到及时沟通共享,并在全局更新时基于非支配排序与拥挤距离优化淘汰机制,平衡全局搜索和局部开发能力,提高了收敛速度和收敛精度.最后,利用孤立度量改进Eps领域,并利用TCCO优化DBSCAN聚类,自适应确定参数,提高了聚类精度和效率.在八个UCI数据集上进行测试,仿真结果表明,提出的TCCO-DBSCAN算法与CO-DBSCAN,SSA-DBSCAN,DBSCAN,KMC方法相比,F-Measure,ARI,NMI指标均有明显提升,且聚类精度更优.通过激光雷达点云数据障碍物聚类的实验验证,证明TCCO-DBSCAN能够有效地适应点云数据密度变化,获得更好的道路障碍物聚类效果,为辅助驾驶中障碍物检测提供支持.
