Some Annual Variation Characteristics for the Northern Hemispheric Monthly Mean Precipitation Fields

By the utilization of monthly precipitation data from all stations in the Northern Hemisphere annexed to the 'World Survey of climatology, Vol. 1-15', the distributions of the maximum precipitation months (MPM), the annual relative precipitation (ARP) and the monthly relative precipitation (percent of annual) in January and July are respectively mapped. Moreover the distributions of intermonthly relative precipitation variabilities from January to December are plotted as well. From these figures, the precipitation in the Northern Hemisphere may be classified into three types(continental, oceanic and transitional types) and 17 regions. The precipitation regime may also be divided into two patterns, the global and regional patterns. The global pattern consists of planetary front system and ITCZ and its inter-monthly variation shows the north-and-south shift of the rain belt; the regional pattern consists of the sea-land monsoon and plateau monsoon regime, in which the inter-monthly variation of rain belt shows a east-and-wcst shift.

Climatic characteristics of high temperature in East China during 1961-2005

Based on the daily maximum temperature data covering the period 1961-2005, temporal and spatial characteristics and their changing in mean annual and monthly high temperature days（HTDs）and the mean daily maximum temperature（MDMT）during annual and monthly HTDs in East China were studied.The results show that the mean annual HTDs were 15.1 and the MDMT during annual HTDs was 36.3℃in the past 45 years.Both the mean annual HTDs and the MDMT during annual HTDs were negative anomaly in the1980s and positive anomaly in the other periods of time,oscillating with a cycle of about 12-15 years.The mean annual HTDs were more in the southern part,but less in the northern part of East China.The MDMT during annual HTDs was higher in Zhejiang,Anhui and Jiangxi provinces in the central and western parts of East China.The high temperature process（HTP） was more in the southwestern part,but less in northeastern part of East China.Both the HTDs and the numbers of HTP were at most in July,and the MDMT during monthly HTDs was also the highest in July.In the first 5 years of the 21st century,the mean annual HTDs and the MDMT during annual HTDs increased at most of the stations,both the mean monthly HTDs and the MDMT during monthly HTDs were positive anomalies from April to October,the number of each type of HTP generally was at most and the MDMT in each type of HTP was also the highest.

Near-surface structure and energy characteristics of the Antarctic Circumpolar Current

Historical surface drifter observations collected from the Southern Ocean are used to study the near-surface structure, variability, and energy characteristics of the Antarctic Circumpolar Current （ACC）. A strong, nearly zonal ACC combined with complex fronts dominates the circulation system in the Southern Ocean. Standard variance ellipses indicate that both the Agulhas Return Current and the East Australian Warm Current are stable supplements of the near-surface ACC, and that the anticyclonic gyre formed by the Brazil warm current and the Malvinas cold current is stable throughout the year. During austral winter, the current velocity increases because of the enhanced westerly wind. Aroused by the meridional motion of the ACC, the meridional velocity shows greater instability characteristics than the zonal velocity does over the core current. Additionally, the ACC exhibits an eastward declining trend in the core current velocity from southern Africa. The characteristics of the ACC are also argued from the perspective of energy. The energy distribution suggests that the mean kinetic energy （MKE）, eddy kinetic energy （EKE）, and are strong over the core currents of the ACC. However, in contrast, EKE/MKE suggests there is much less （more） eddy dissipation in regions with strong （weak） energy distribution. Both meridional and zonal energy variations are studied to illustrate additional details of the ACC energy characteristics. Generally, all the energy forms except EKE/MKE present west-east reducing trends, which coincide with the velocity statistics. Eddy dissipation has a much greater effect on MKE in the northern part of the Southern Ocean.

基于改进K-means聚类的轨道交通基础设施分布式光伏发电典型场景生成及出力特性分析

受限于自然条件,光伏出力具有很强的随机性。为准确评估轨道交通基础设施分布式光伏发电的光伏出力特性,提出一种基于改进K-means聚类算法的轨道交通基础设施分布式光伏发电典型场景生成方法,并基于此进行光伏出力特性分析。首先,基于分布式光伏发电设施以及气象数据,利用PVsyst软件模拟光伏发电出力数据。然后,针对基本K-means聚类算法聚类参数和初始聚类中心盲目性高的问题,结合聚类有效性指标(Density based index,DBI)和层次聚类对其进行改进并利用改进K-means聚类算法生成光伏典型日出力场景。最后,基于华中地区某地轨道交通基础设施分布式光伏系统对所提方法的有效性和优越性进行验证,并通过定性和定量分析各典型场景的出力特性揭示轨道交通基础设施分布式光伏出力的规律和特点。

The hydrochemical characteristics and its significance of geothermal water in both sides of large fault: Taking northern section of the Liaokao fault in north China as an example

Based on comparative analysis on hydrochemical characteristics of geothermal water in the north part of Liaokao fault,this research focuses on studying the indicative significance of hydrochemical characteristics for the formation of geothermal water.The result shows that:(1)There is no obvious hydraulic connection between the karst geothermal water(occurred in the east part of the Liaokao fault)and the sandstone geothermal water(occurred in the west part of Liaokao fault).(2)In a close hydrological environment,caused by tectonic activities,geothermal water remains longer time in reservoir,hence the water-rock interaction is more complete,with high degree of concentrations,whereas the renewable capacity of the water is weaker.(3)There is no high temperature mantle source fluid mixed in the geothermal water.Karst geothermal water occurred deep circulatory convection along Liaokao fault and its secondary fault,therefore there is deep crust source fluid added into the geothermal water,closer to the Liaokao fault,the greater affected by the deep crust fluid.However,sandstone geothermal water has weak deep circulatory convection.

Analysis on the psychological characteristics of patients with acute iridocyclitis

【正】Dear Sir,I am Dr.Wei Sun,from the Department of Ophthalmology,the Fourth Affiliated Hospital of China Medical University,Eye Hospital of China Medical University,shenyang,Liaoning Province,China.I write to present our study on the psychological characteristics of patients with acute iridocyclitis.Studies showed stimulation from patient’s external environment could influence their psychological state,persisting neural endocrine disorders that might lead to a series of physiological and psychological changes in the human body[1-6].It was confirmed many ocular diseases were

Connotations and Internal Cultural Meanings of Chinese Jade in Chu Culture at Pre-Qin Period

The thesis conducts its analysis fromthe perspective of cultural characteristics of Chu state of Pre-Qin period in ancient China.The culture of Chu,usually focusing on ceremony sacrifice and several other activities,presents unique characteristics of the development of Chinese society and culture.Actually,the jade artifact at that time shows cultural features both at artistic and spiritual level and bears prominent cultural connotations like national spirit of solemnness and generosity.Chinese jade of Chu state of Pre-Qin period due to its abundant cultural connotations and meanings,poses to be an essential element of traditional Chinese culture,which shows artistic and national features of traditional jade culture and can directly influence development of modern society and culture.

基于改进K-Means算法的电动汽车充电负荷特性分析

电动汽车充电行为具有较大的随机性,一定程度上影响电网的稳定运行和规划。为更准确地分析电动汽车充电负荷的特性,提出一种基于改进K-Means算法的聚类分析方法。针对K-Means算法在初始聚类中心选取上的随机性和不稳定性,首先利用Mini Batch K-Means算法的随机抽样能力优化初始聚类中心的选择,随后结合K-Means算法进行迭代优化,有效解决K-Means算法聚类结果不稳定的问题。以云南某城市充电桩负荷数据进行算例分析,结果表明,所提算法相比传统方法相比能更加准确地对多个不同负荷特性的用户进行分类,从而更有效地指导有序用电管理策略的制定。

基于空间约束K⁃means模型的长三角地区生态系统服务时空格局及功能分区研究

科学认知生态服务功能的时空演变规律以及合理划分生态系统服务簇的空间分类对于生态系统管理和政策制定至关重要。旨在揭示长三角城市群2000—2020年间生物多样性维护、产水量、碳储存、土壤保持、植被净初级生产力、粮食产量的时空演变特征、权衡关系,并利用空间约束K⁃means模型(SC K⁃means)聚类识别生态系统服务簇,划分生态系统服务功能管理区。研究结果表明:(1)生物多样性维护、产水量、碳储存、土壤保持、植被净初级生产力整体呈“西南山地高,东北平原低”空间格局,粮食产量与之相反;(2)六类生态系统服务空间变化差异体现出明显人类活动与自然气候主导,且粮食产量与其他生态系统服务表现为权衡关系;(3)基于SC K⁃means识别生态系统服务簇的结果将研究区划分为为粮食主产区、人类活动密集区、皖浙生态保护区、大别山生态保护区、皖江生态过渡带、长三角核心保护区六类生态功能区,针对各分区提出差异化生态管控建议。研究可为国土空间规划分区引导提供理论依据与实践参考。

The New Detection and the Basic Characteristics of the Structural System of Taiwan Region of China—Using the Earth Satellite's Remote-sensing Images to Explain the Structural System of Taiwan Region of China

This text uses the regional geological investigation data and the remote sensing image data of earth-satellite remote sensing to synthetically analyze the structural system of Taiwan region of China. Authors detection-marked and assurance-marked and divided 5 kinds of structural system of the Taiwan region: (1) the wreath-shaped structural system, (2) the N-N-E oriented structural system, (3) the S-N oriented structural system, (4) the N-E oriented structural system, (5) the arc-shaped structural system. Combination of the texture faces and associated method were adopted to recover and reconstruct the structural evolution sequences and the formation periods. In this paper, problems such as the development process in geology etc. are also discussed, contributing new information to research the structural field of the East Asia and its tectonic plate movements and structural actions inside the land plate .

基于K-Means聚类方法的北京市公共交通通勤乘客特征挖掘

北京市公共交通系统在满足居民出行需求的同时,产生海量的出行数据,为客流分析奠定数据基础,而地理信息技术、机器学习为数据处理与分析提供新的思路。基于2021年10月北京1周公共交通票务数据,通过多种清洗手段和补全算法对源数据进行处理,通过时间阈值和空间阈值提取出行链,从时间、空间、频次3个维度分析客流特性并构建聚类变量。采用K-Means算法将常乘客分为5类,分析各类别乘客特征规律,提取出稳态常乘客类别,为常乘客的分析提供新的思路,有助于界定公交的主要客流来源出行特征,为改善公交运营,提升公交服务水平提供支撑。

跟踪窗自适应的Mean Shift目标跟踪算法

针对Mean Shift算法不能很好地跟踪尺度变化目标的缺点,提出一种将Mean Shift算法和目标几何特征相结合的目标跟踪算法。该方法在Mean Shift框架下提取目标的几何特征,根据目标的面积和型心坐标对跟踪窗的位置和大小进行修正,最后更新Mean Shift的目标模板。通过大量实验仿真证明,改进的算法能很好地跟踪尺度变化的目标,对目标的仿射变化和非刚性的形态变化具有有效性和鲁棒性。

融合K-means与高斯混合模型的驾驶风格聚类研究

为研究驾驶员的跟车特性,探究驾驶员风格划分方法,采集50名驾驶员的实车试验数据,选取平均跟车时距和平均制动时距为二维向量,建立基于K-means聚类结果的高斯混合模型(GMM)并分析不同风格驾驶员的聚类结果。研究表明:样本数据聚为3类时的平均轮廓系数为0. 45,将驾驶员划分为冒进型、平稳型、保守型3类时聚类效果较好;冒进型驾驶员倾向于选择较小的跟车时距和制动时距,保守型驾驶员的跟车及制动时距则普遍较大,模型聚类结果更加柔性,样本区分度更高。

基于K-means聚类的路面裂缝分割算法

针对传统分割算法在非均匀背景中存在低抗噪性及高复杂性的问题,将聚类分析和区域生长算法相结合,提出基于K-means聚类的路面裂缝区域生长分割算法。依据图像灰度像素特征进行裂缝目标聚类,融合裂缝几何纹理特征将聚类中心值作为种子点区域生长,经过形态学滤波优化处理完成精确分割。仿真结果表明,该算法在视觉上裂缝分割的准确率提高,查准率曲线和受试者工作特征曲线的评价结果也表明,该算法与传统边缘检测算法相比,具有环境适应能力强、识别准确率高以及性能稳定等优势。

基于K-means算法的无线传感器网络节点自私行为检测方法

针对无线传感网络共享信道中自私节点(或恶意节点)对信道的不公平竞争行为,提出了一种基于网络性能特征序列的聚类检测方法(Network Performance Characteristic Sequence based-Clustering Detection Method,NPCS-CDM)。该算法以节点链路的平均传输延迟和平均吞吐量为网络性能特征建立统计序列,采用K-means聚类算法对特征序列进行分析和聚类,以此完成网络中节点自私行为的检测,同时该方法有效解决了基于CUSUM算法用于检测多自私节点的不足,即难以确定适当的阈值来完成检测任务。基于NS2的仿真结果表明,NPCS-CDM对自私节点的检测效果明显优于已有的基于CUSUM的算法,而且能适用于多自私节点存在的情况。

基于改进K-Means聚类和BP神经网络的台区线损率计算方法

配电网线损管理中面临的主要问题有表计配置不齐备、运行数据不易收集、元件和节点数过多。这些问题导致线损率计算工作十分繁杂。提出了一种基于改进K-Means聚类算法和Levenberg-Marquardt(LM)算法优化的BP神经网络模型快速计算低压台区线损率的方法,并通过编程加以实现。根据样本的电气特征参数,提出了改进K-Means聚类算法,将台区样本分类,解决了台区线损率数值分散的问题。在此基础上,采用LM算法优化的BP神经网络模型对样本数据按类进行训练,利用BP神经网络拟合样本线损率与电气特征参数之间的关系,得到其变化规律。以某地区601个台区样本数据为例进行仿真计算,验证了所提方法的准确性。结果表明,与标准BP神经网络模型相比,LM算法优化的BP神经网络模型具有快速收敛、高精度等优点。

主成分分析和K-means聚类在说话人识别中的应用

为了解决特征提取计算量大且特征参数不够全面的问题,提出了用主成分分析和K-means聚类进行语音特征参数提取的方法。通过对说话人识别系统中最常用的线性预测倒谱系数(LPCC)参数和梅尔倒谱系数(MFCC)参数提取原理以及差分参数的提取算法深入研究,选择LPCC、MFCC以及其一阶差分参数的组合作为最终混合特征参数。首先用主成分分析降低每一帧语音信号特征参数的阶数,然后经过K-means聚类降低帧数,最后通过矢量量化(VQ)来进行说话人识别。实验结果表明,该方法降低了计算复杂度,同时也提升了识别准确性。

一种应用复杂网络特征的K-means初始化方法

K-means算法是一种基于划分的聚类算法,具有算法简单且收敛速度快的特点。但该算法的性能依赖于聚类中心的初始位置的选择。拓展了复杂网络的重要特征,针对带有属性的数据对象所构成的数据集,定义了多维属性对象的度、聚集度和聚集系数,选取度和聚集系数高的K个点作为K-means聚类的初始中心点。实验数据表明,改进后的K-means算法较传统的算法具有更高的效率和准确度。

基于局部高度与Mean Shift的三维模型信息隐藏算法

针对基于载体的秘密通信的需求,提出利用模型点Mean Shift聚类分析的三维模型载体信息隐藏算法。该算法将局部高度引入到模型点显著性衡量中,用以描述顶点的能量和结构特性,并用Mean Shift聚类分析法将各个顶点按照局部高度值分为能量特性不同的3类。以3类顶点为载体,采用隐藏信息与载体能量特性匹配的方式,通过修改3类顶点的结构特性指标,实现不同信息的嵌入。实验结果显示,该算法各项性能均衡,尤其具有较好的抗分析性和感知篡改性,且嵌入容量较大。

基于模糊逻辑的K-means算法研究

K-means算法的基本思想是通过迭代方法把所有的元素都唯一聚类到不同的簇中,使得同一簇中的质点具有最小相异度,不同簇间的元素具有最大相异度。但是,这种聚类方法使得那些属于不同簇的交叉区域中的质点也被简单地聚类到了某个簇中,因此无法表达某些元素的跨簇特性。本文提出了基于模糊逻辑的K-means算法,利用模糊逻辑来计算不同簇交叉区域中质点属于某个簇的权重,在获得聚类结果的同时可以有效描述质点的跨簇特性。实验结果表明该算法是有效的。