Evaluation on Radar Reflectivity-Rainfall Rate (Z-R) Relationships for Guyana

The constant development of science and technology in weather radar results in high-resolution spatial and temporal rainfall estimates and improved early warnings of meteorological phenomena such as flood [1]. Weather radars do not measure the rainfall amount directly, so a relationship between the reflectivity (Z) and rainfall rate (R), called the Z-R relationship (Z = aRb), where a and b are empirical constants, can be used to estimate the rainfall amount. In this research, mathematical techniques were used to find the best climatological Z-R relationships for the Low Coastal Plain of Guyana. The reflectivity data from the S-Band Doppler Weather Radar for February 17 and 21, 2011 and May 8, 2012 together with the daily rainfall depths at 29 rainfall stations located within a 150 km radius were investigated. A climatological Z-R relationship type Z = 200R1.6 (Marshall-Palmer) configured by default into the radar system was used to investigate the correlation between the radar reflectivity and the rainfall by gauges. The same data sets were used with two distinct experimental Z-R relationships, Z = 300R1.4 (WSR-88D Convective) and Z = 250R1.2 (Rosenfeld Tropical) to determine if any could be applicable for area of study. By comprehensive regression analysis, New Z-R and R-Z relationships for each of the three events aforementioned were developed. In addition, a combination of all the samples for all three events were used to produce another relationship called “All in One”. Statistical measures were then applied to detect BIAS and Error STD in order to produce more evidence-based results. It is proven that different Z-R relationships could be calibrated into the radar system to provide more accurate rainfall estimation.

Understanding the Variability of Z-R Relationships Caused by Natural Variations in Raindrop Size Distributions(DSD):Implication of Drop Size and Number

In the issue of rainfall estimation by radar through the necessary relationship between radar reflectivity Z and rain rate R (Z-R), the main limitation is attributed to the variability of this relationship. Indeed, several pre-vious studies have shown the great variability of this relationship in space and time, from a rainfall event to another and even within a single rainfall event. Recent studies have shown that the variability of raindrop size distributions and thereby Z-R relationships is therefore, more the result of complex dynamic, thermody-namic and microphysical processes within rainfall systems than a convective/stratiform classification of the ground rainfall signature. The raindrop number and size at ground being the resultant of various processes mentioned above, a suitable approach would be to analyze their variability in relation to that of Z-R relation-ship. In this study, we investigated the total raindrop concentration number NT and the median volume di-ameter D0 used in numerous studies, and have shown that the combination of these two ‘observed’ parame-ters appears to be an interesting approach to better understand the variability of the Z-R relationships in the rainfall events, without assuming a certain analytical raindrop size distribution model (exponential, gamma, or log-normal). The present study is based on the analysis of disdrometer data collected at different seasons and places in Africa, and aims to show the degree of the raindrop size and number implication in regard to the Z-R relationships variability.

分类发包与规制性治理:中国基层社会治理中的政社关系演变及其机制研究

政府主导下的社会组织参与是基层社会治理的重要内容。现有研究大多关注“国家-社会”关系框架下的规范层面,较少从历史维度探讨基层社会治理中的政社关系演变及其内在逻辑。本文基于行政发包理论,提出分类发包下的规制性治理框架,将政社关系纳入基层社会治理进程中进行分析发现,不同时期的任务包决定了基层政府政策制定的共性和差异化特征,在与其他主体的互动中形成了国家主导下的规制性治理。其中,政府与社会组织间的关系经历了从严格管理到分类管理再到党建全面引领发展的转变,呈现了中国特色的社会组织发展进路。分类发包是其主要形成机制,不同阶段的社会组织发展水平、经济社会发展状况等情境是基层治理实践的约束性因素。规制性治理的提出深化了中国社会组织管理研究,为社会组织参与基层治理的整体性解释提供了可能。

Expert Classification Method Based on Patch-Based Neighborhood Searching Algorithm

The expert knowledge has been widely used to improve the remotely sensed classification accuracy. Generally, the ex-pert classification system mainly depends on DEM and some thematic maps. The spatial relationship information in pixel level was commonly introduced into the expert classification. Because the geographic objects were found spatially dependent relationship to a certain degree, the commonly used basic unit of spatial relationship information in pixel greatly limited the efficiency of spatial in-formation. A patch-based neighborhood searching algorithm was proposed to implement the expert classification. The homogene-ous spectral unit, patch, was used as the basic unit in the spatial object granularity, and different types of patches' relationship in-formation were obtained through a spatial neighborhood searching algorithm. And then the neighborhood information and DEM data were added into the expert classification system and used to modify the primitive classification errors. In this case, the classi-fication accuracies of wetland, grassland and cropland were obviously improved. In this work, water was used as base object, and different types of water extraction methods were tested to get a result in a high accuracy.

Consistency in <i>Z</i>-<i>R</i>Relationship Variability Regardless Precipitating Systems, Climatic Zones Observed from Two Types of Disdrometer

Data from rain Drop Size Distributions gathered on five sites in Africa as well as those of the pilot site in Kourou (French Guyana, South America), located in different climatic zones, and collected by two types of disdrometer (the impact JW RD-69 disdrometer and the Optical Spectro-Pluviometer, OSP) are used to study the consistency of the reflectivity factor-rain rate at the ground (Z-R) relationship variability. The results clearly confirm that the relationship Z-R knows a large spatial variability, from a type of precipitation to another and within the same precipitation regardless the type of disdrometer used for DSD measurements. Base on the similarity of the relations reflectivity factor-rain rate and ratio median volume diameter over the total number of drops-rain rate, the variability of the Z-R coefficients (A, b) through the simultaneously implication of the size and number of drops which characterize the DSD was exhibited. It was shown that the relationships A-α and b-β designed to understand the involvement of parameters D0 and NT of DSD in the variability of the relationship Z-R are similar regardless the types of disdrometer used. However, the relations A-α in the Sahelian region appear to deviate from those of Guinean, equatorial and Soudanian zones. The plausible reasons were discussed.

Radar Quantitative Precipitation Estimation Based on the Gated Recurrent Unit Neural Network and Echo-Top Data

The Gated Recurrent Unit(GRU) neural network has great potential in estimating and predicting a variable. In addition to radar reflectivity(Z), radar echo-top height(ET) is also a good indicator of rainfall rate(R). In this study, we propose a new method, GRU_Z-ET, by introducing Z and ET as two independent variables into the GRU neural network to conduct the quantitative single-polarization radar precipitation estimation. The performance of GRU_Z-ET is compared with that of the other three methods in three heavy rainfall cases in China during 2018, namely, the traditional Z-R relationship(Z=300R1.4), the optimal Z-R relationship(Z=79R1.68) and the GRU neural network with only Z as the independent input variable(GRU_Z). The results indicate that the GRU_Z-ET performs the best, while the traditional Z-R relationship performs the worst. The performances of the rest two methods are similar.To further evaluate the performance of the GRU_Z-ET, 200 rainfall events with 21882 total samples during May–July of 2018 are used for statistical analysis. Results demonstrate that the spatial correlation coefficients, threat scores and probability of detection between the observed and estimated precipitation are the largest for the GRU_Z-ET and the smallest for the traditional Z-R relationship, and the root mean square error is just the opposite. In addition, these statistics of GRU_Z are similar to those of optimal Z-R relationship. Thus, it can be concluded that the performance of the GRU_ZET is the best in the four methods for the quantitative precipitation estimation.

Statistical Characteristics of Raindrop Size Distribution in the South China Monsoon Region(Guangdong Province)

While heavy rainfall frequently takes place in southern China during summer monsoon seasons,quantitative precipitation forecast skills are relatively poor.Therefore,detailed knowledge about the raindrop size distribution(DSD)is useful in improving the quantitative precipitation estimation and forecast.Based on the data during 2018-2022 from 86stations in a ground-based optical disdrometer measurement network,the characteristics of the DSD in Guangdong province are investigated in terms of the particle size distribution(N(D)),mass-weighted mean diameter(Dm) and other integral DSD parameters such as radar reflectivity(Z),rainfall rate(R) and liquid water content(LWC).In addition,the effects of geographical locations,weather systems(tropical cyclones,frontal systems and the summer monsoon) and precipitation types on DSD characteristics are also considered.The results are shown as follows.1) Convective precipitation has a broader N(D) and larger mean particle diameter than the stratiform precipitation,and the DSD observations in Guangdong are consistent with the three-parameter gamma distribution.The relationships between the Z and R for stratiform and convective precipitation are also derived for the province,i.e.,Z=332.34 R1.32and Z=366.26R1.42which is distinctly different from that of the Next-generation Weather Radar(NEXRAD) Z-R relationship in United States.2) In the rainy season(April-September),the Dm, R and LWC are larger than those in the dry season(OctoberMarch).Moreover the above parameters are larger,especially in mid-May,which is the onset of the South China Sea summer monsoon.3) The spatial analysis of DSD shows that the coastal station observations indicate a smaller Dmand a larger normalized intercept parameter(log10Nw),suggestive of maritime-like rainfall.Dmis larger and log10Nwis smaller in the inland area,suggestive of continental-like rainfall.4) Affected by such weather systems as the tropical cyclone,frontal system and summer monsoon,the DSD shows characteristics with distinct differences.Furthermore,frontal system rainfall tends to present a continental-like rainfall,tropical cyclone rainfall tends to have a maritime-like rainfall,and summer monsoon rainfall characteristic are between maritime-and continental-like cluster(raindrop concentration and diameter are higher than continental cluster and maritime cluster,respectively.)

基于混淆矩阵和Fisher准则构造层次化分类器

构造层次化分类器的首要环节是确定各个子分类器的层属关系及其内部组成.从模式间的相似关系入手,实现了一种自动产生层次化分类器结构的方法.为了描述模式间的相似关系,首先提出利用混淆矩阵度量相似性的思路与方法,避免了现有常用度量方法计算量大、假设条件难以成立的不足.进而遵循Fisher准则,设计并实现了模式相似关系分析机(patterns’similarityrelationshipanalyzingmachine,简称PSRAM),将有师指派和无师自组两种常用的模式重组方法有机结合起来,自适应地产生层次化分类器结构.大量测试证实,该方法有效、实用,可以显著地提高分类器的识别性能和稳健性.

利用RAPD标记研究几种淡水腹足类的亲缘关系

以软体动物腹足纲、中腹足目的光滑狭口螺、长角涵螺、纹沼螺、赤豆螺、大沼螺几个形态分类的近缘种及梨形环棱螺 (对照 )作为研究对象 ,用随机扩增多态DNA技术对上述动物进行了 2 0个引物的扩增 ,共获得 1 1 7条扩增谱带 ,单个引物扩增的RAPD标记在 3～ 1 2个之间 ,片段长度在 34 0～ 30 0 0bp之间。试验结果显示 :淡水螺类的RAPD标记具有明显的多态性 ,而且种间的扩增标记及差异程度可以反映出物种间系统演化过程的亲缘关系。通过数值聚类制图后得到 :长角涵螺、纹沼螺、大沼螺、赤豆螺之间的亲缘关系较近 ,而光滑狭口螺、梨形环棱螺与上述 4个种的亲缘关系较远 ,其结果与新修订的淡水中腹足目科级分类方案相当吻合。

分组Z-I关系及其在淮河流域雷达测雨中应用

本文使用713雷达及其数字化终端，对淮河正阳关以上流域进行了定量测量降雨的试验。用最优化处理方法，按DBZ值大小分组统计，得到了这一地区Z-I关系的序列。然后，用这组关系得到降雨的雷达估算值。试验结果表明，距雷达50－100km之间的区域雷达定量测雨的精度较好。和雨量计测值比较，雷达估算的单站一小时雨量的平均相对误差为46％，单站过程雨量的平均相对误差为30％。雷达定量测雨可以作为常规雨量站网的补充，准实时地提供多种雨情信息。

基于上下文的在线草图识别方法

支持用户自由连贯地绘制草图是在线草图识别研究的目标之一。本文提出一种使用空间关系等上下文和贝叶斯分类器进行草图识别的方法,其主要特点包括两个方面:第一,使用笔画空间关系进行自动笔画成组,可以在不打扰用户绘图的情况下完成候选符号的选取;第二,利用贝叶斯分类器实现在线草图识别,可以解决识别方法的领域相关性及画法敏感性问题。实验验证了方法的有效性。

抗艾滋病药物环尿素类化合物的结构表征及其生物活性的定量预测

提出一种新的结构描述子———按氢分类的电距矢量 (H MEDV) ,并用于环尿素类化合物抗人类免疫缺陷病毒(humanimmuno deficiencyvirus,简称HIV)活性预测 ,籍以多元线性回归 (MLR)建立了H MEDV与活性之间的相关模型 ,取得了良好的结果 ,相关系数达R =0 .971.另外采用逐步回归 (SMR)从原模型参数中选取了 5个参数建立一新模型 ,其模型相关系数为R =0 .938;继以留一法 (Leave one out,LOO)进行交互检验 ,相关系数与之接近 ,R =0 .90 8;说明了定量结构活性相关模型具有很好的稳定性和预测能力 .

分类型最优法在江苏沿江地区降水估测中的应用与讨论

为提高现有天气雷达产品生成模块中处理系统算法精度、并为其他短时临近预报系统或数值预报模式提供合适的Z-I关系为目的,选择江苏沿江地区作为试验区域,采用分类型最优法建立相应的Z-I关系,并比较分类型最优法与单一Z-I关系对过程雨量和分段雨量的估测能力。结果表明:分类型最优法比单一Z-I关系法明显提高过程雨量估测的精度,梅汛期降水估测精度提高近2.5倍,夏季台风降水估测由低估72%降低至低估45%。对不同雨量段进行估测比较后发现,分类型最优法对强降水雨量段改善较为明显,对雨强>10 mm/h的梅汛期对流云降水和台风降水所有雨量段的雨量估测改善明显。最后在气候统计的基础上,通过改进雷达估测降水产品色标数值等级,以达到优化雷达估测降水产品图像的显示能力。

基于高斯混合模型和AdaBoost的夜间车辆检测

针对夜间车辆检测精度相对不高的问题,提出通过构建车头灯对空间几何关系的高斯混合模型(GMM)和采用逆投影车辆样本的Ada Boost分类器准确检测夜间车辆的方法。首先,在交通场景中根据车头灯对的空间位置关系设置逆投影面,通过图像预处理粗定位车灯区域;其次,在逆投影图像下利用车头灯对的空间几何关系构建车灯对的高斯混合模型,初步匹配车头灯对;最后,采用逆投影车辆样本,利用Ada Boost分类器进一步准确检测车辆。实验在3个交通场景的检测结果表明,与原始图像下的Ada Boost方法相比,所提方法的检测率提高了1.93%,漏检率降低了17.83%,误检率降低了27.61%;与D-S(Dempster-Shafer)证据理论方法相比,检测率提高了2.03%,漏检率降低了7.58%,误检率降低了47.51%。所提方法提高了相对检测精度,减少了地面反光和影子等的干扰,满足交通场景中夜间车辆检测的可靠性和准确性的要求。

专利分类号耦合分析在企业潜在合作关系识别中的应用

[目的/意义]企业间的技术相似性能否转化为现实的合作关系,专利耦合所揭示的潜在关联究竟预示着合作还是竞争,这些问题需要在实证研究中寻找答案。[方法/过程]以德温特专利分类号为媒介构建专利耦合网络,采用可视化和因子分析方法考察企业的技术相似性及其聚类结构、发掘技术派系及其研究方向,对专利耦合网络与现实合作网络进行比较。[结果/结论]单纯的技术相似性不能作为潜在合作关系的有效判定依据,基于专利耦合形成的潜在合作关系难以转化为现实,社会关系因素对于专利合作的影响程度远甚技术相似性。

地震模拟试验中单质点体系小比例尺模型的分级相似关系

在地震模拟试验中采用逐级加载的加载方式给试验结果带来较大误差.试验结果表明对一个模型采用逐级加载方式至大震输入后,其层间位移角为1/50;而对模型直接大震输入,其层间位移角为1/80,采用逐级加载的试验结果致使我们错误的估计原型的抗震性能;在逐级加载的地震模拟试验中,采用分级相似关系能减小逐级加载试验方式给结果带来的误差,从振动台试验加速度反应看误差达到6%左右,从位移反应上看,采用分级相似关系后,位移反应与直接进行大震试验结果较为接近.

基于RBF神经网络的客户分类模型

运用径向基函数(RBF)神经网络和K均值聚类算法建立了客户价值分类模型,并用最小二乘法调整RBF的权值.仿真结果证明了该方法的有效性.

HMEDV描述法对氨基喹啉类抗疟药活性预测

目的:研究氨基喹啉类化合物抗疟原虫活性的定量构效关系。方法:应用按氢分类的分子电距矢量描述40个氨基喹啉类化合物的分子结构,运用多元线性回归方法,对其抗疟原虫活性进行定量构效关系研究。结果:对于两组抗疟原虫活性数据所得结果相关系数分别为0．920和0．910。结论:说明所建立的多参数模型稳定并具有良好的估计和预测能力。

一种改进的贝叶斯分类器剪接位点预测

虽然现有的DNA剪接位点辨识算法取得很高的辨识精度,但是大多数方法计算量很大。朴素贝叶斯分类器是一种简单而高效的分类器,但是它的属性独立性假设使其无法表示现实世界属性之间的依赖关系,影响了它的分类性能。将朴素贝叶斯分类器进行改进,推导出决策属性和各条件属性对数值间存在线性关系,并用最小二乘法求出这种线性关系系数,设计出一种新的贝叶斯分类器。将改进的贝叶斯分类器应用于DNA序列剪接位点的辨识中。仿真结果表明,本算法计算时间和测试样本的数量成线性关系,辨识精度较朴素贝叶斯分类器有明显提高,同时高于现有辨识算法。

基于专利权人-分类号耦合分析的潜在合作关系网络研究

提出面向专利文献的专利权人-分类号耦合分析方法,用于考察专利权人之间基于分类号耦合而形成的潜在合作关系。以近五年太阳能汽车技术领域的德温特专利为例,构建耦合矩阵并进行可视化分析,将潜在合作关系网络与现实合作关系网络进行比较,对潜在合作关系网络开展因子分析,并将其结果进行可视化展示。结果表明,对于专利文献来说,潜在合作关系比现实合作关系更为普遍,且包含更为丰富的情报信息。专利权人-分类号耦合分析能够同时揭示合作与竞争两种潜在的关系。基于因子分析结果而进行的网络可视化分析能够呈现出更为明显的聚类效果,可以作为专利权人-分类号耦合分析的有效补充。在太阳能汽车领域日本的技术优势非常明显,在关键技术领域日本企业继续保持全球领先水平。中国拥有的专利总量居于世界前列,但中国企业个体的技术力量却相对单薄,尤其在核心技术领域仍处于劣势。