Discriminate Analysis for Dust Storm Prediction in the Gobi and Steppe Regions in Mongolia

A discriminate analysis method for probability forecast of dust storms in Mongolia has been developed. The prediction method uses data recorded at 23 meteorological stations in the Gobi and steppe regions of Mongolia, including surface air pressure and geo-potential height at the 500-hPa level on grid points, and weather maps from 1975 to 1990. Weather elements such as air temperature, pressure, geo-potential height etc, which influence the formation of dust storms, are prepared as predictors. To select the most informative/important predictors (variables), we used a mean correlation matrix of variables together with the Mahalonobis distance, and correlation coefficients between dust storms and predictors with an orthogonalization for removing correlated predictors. The most informative predictors for dust storm prediction are intensities of surface cyclones and migratory anticyclones, passage of cold fronts, the horizontal gradients of the surface air pressure in the cold frontal zone, cyclonic circulations from the ground surface up to the 500-hPa level, the geo-potential height at 500-hPa level and its temporal changes. Selected predictors are used in discriminate analysis for formulating dust storm prediction equations. Sandstorm data have been classified into three classes, viz., strong, moderate and weak dust storms, depending on their intensities, durations and areas covered. Predictions of the probabilities of dust storm occurrence use the prediction equations for each class. The prediction is made from 12 hours to 36 hours. Verification of the probability forecasts of dust storms is also shown. The accuracy of forecasts is 72.2–79.9% with the data used for developing equations (dependent variables), in contrast to 67.1–72.0% with unrelated data for deriving equations (independent variables).     

COMPARING METHODS OF HYDROLOGIC REGIONALIZATION1

ABSTRACT: Data splitting is used to compare methods of determining “homogeneous” hydrologic regions. The methods compared use cluster analysis based on similarity of hydrologic characteristics or similarity of characteristics of a stream's drainage basin. Data for 221 stations in Arizona are used to show that the methods, which are a modification of DeCoursey's scheme for defining regions, improve the fit of estimation data to the model, but that is is necessary to have an independent measure of predictive accuracy, such as that provided by data splitting, to demonstrate improved predictive accuracy. The methods used the complete linkage algorithm for cluster analysis and computed weighted average estimates of hydrologic characteristics at ungaged sites.     

广西海域优先关注问题甄别及对策探讨

《广西北部湾经济区发展规划》已获得国务院批准实施,广西沿海地区进入了快速发展时期。在经济快速发展过程中,海洋环境污染、海洋生态损害、海洋灾害、海洋物理条件改变、海洋环境管理等方面的问题都会存在。针对不同环境问题对食品安全、人群健康、海洋资源、生态系统健康、其他经济和社会价值（如文化价值）等方面的影响,通过采用表格法和权重法,甄别广西海洋优先关注问题,确定各类环境问题优先关注次序,针对这些问题,提出相应的对策。     

江苏省城市人居环境定量评价分析

城市人居环境质量定量评价指标体系是描述、评价城市居住地域是否安全、舒适、和谐、方便的一套可感知的参数集合,是评价居住地域可居性、持续性的重要依据。本文通过城市人居环境指标体系的构建以及主成分和因子分析、聚类和判别分析的方法,来研究江苏省地区城市人居环境的质量,把江苏省在苏南、苏中、苏北的9个城市分为几个大类,并提出一些针对性的对策建议。     

线性判别分析对舟山海洋站降水中常量阳离子含量的年度、季节特征分析

通过对舟山站点2002/2003年度降水中的6种常量阳离子H⁺、NH₄⁺、K⁺、Na⁺、Ca²⁺、Mg²⁺近2a的连续观测,采用稳健统计分析对浓度范围及变化趋势进行了描述.利用线性判别分析对实验数据进行降维处理,得到线性判别曲面,对样本点在新正规变量空间的时间性分布特征进行了描述,依据正规变量的线性组合,解释了决定该样本点时间性特征分布的主要阳离子影响因素,并对造成异常样品点的影响因素进行了分析.     

小波分析在湖泊常见浮游藻荧光识别测定中的应用

利用Daubechies7（db7）小波函数对27种分属于6个门,22个属的主要湖泊常见浮游藻的三维荧光光谱进行分解,得到各尺度分量及小波分量,应用Bayesian判别分析选择第三层尺度分量（Ca3）作为最佳特征谱,通过系统聚类分析得到浮游藻的标准谱库,结合非负最小二乘法解析的多元线性回归建立湖泊常见浮游藻的荧光识别测定技术.将该技术用于单种藻样品、模拟混合样品及实际混合样品的识别分析,单种藻样品在门类水平上的识别正确率平均为98.6%,识别测定的平均相对含量为90.8%.在实验过程中加入一定比例的噪声,考察了标准谱库的抗噪能力.对于104个实验室混合样品,优势门的藻在门类水平上的平均识别正确率为97.0%,识别的平均相对含量为67.7%,次优势门的藻在门类水平上的平均识别正确率为90.7%,识别的平均相对含量为32.3%.结果表明,所建立的识别测定技术具有可行性.     

变电站复杂声场中多点噪声源的鉴别

复杂声场中单个声源的鉴别和评价是噪声污染控制的重要环节。简要介绍了几种常用的噪声源鉴别方法,然后结合变电站复杂声场中噪声产生的实际情况,针对变电站主要声源噪声的特性提出了两种方法的基本原理和具体操作步骤,即声强测量法和基于波叠加的噪声源识别方法,用以进行变电站中多点噪声源的鉴别。这为建立变电站声场中多点声源鉴别的标准方法提供了可能;对于厂界噪声超过环保部门确定标准的变电站,应用这些方法可以提供明确的治理思路。     

基于Bayes判别模型的火场中铜导线短路熔痕 定量金相鉴定方法研究

借助计算机图像处理技术,改进了定量金相分析方法,测量了20个一次短路熔痕和20个二次短路熔痕的金相组织,对数据进行了主成分分析,提炼出了晶粒特征因子、气孔特征因子和复合因子三个主成分,基于Bayes判别法建立了火场中短路熔痕定量金相分析判别模型,经自身检验和交互检验,准确率均高于80%,充分满足鉴定要求,为更加有效地应用定量金相法鉴别短路熔痕提供了理论依据。