基于BERN5．0软件计算的北京地区GPS可降水量研究

收集了2002-2007年6年期间的北京房山站（BJFS）连续观测数据,利用BERN高精度GPS数据处理软件计算出该站的对流层延迟,再利用该站的气象观测资料分离干延迟获得2mm精度的湿延迟,计算出BJFS站的可降水量（PWV）,组成长达6年的时间序列,初步探讨北京地区的季节性降水量变化,特别是第三季度的可降水量影响,通过数据走势,预测计算不同季度的降水概率。     

Landslide susceptibility zonation method based on C5.0 decision tree and K-means cluster algorithms to improve the efficiency of risk management

Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70％landslide pixels)and validation data(30％landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20％interval of landslide occurrence probability contained 89％of the historical landslides but only accounted for 10.3％of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices.     

岷县-卓尼5.0级地震的基本特征和地质背景研究

归纳总结了岷县-卓尼5．0级地震的基本参数、烈度分布、建筑物震害、发震构造等基本特征,并分析了该地震烈度偏高和震害较重的基本原因。该次地震与2003年11月13日岷县Ms5．2地震基本特征相同,发震构造也相同,为临潭-宕昌断裂带。     

生物土壤结皮铁代谢微生物组成及其功能基因对演替的响应

采用微生物宏基因组学微阵列GeoChip 5.0技术,选择腾格里沙漠东南缘沙坡头地区不同年代人工固沙植被区的生物土壤结皮（BSC）为对象,分析BSC演替过程中参与铁代谢的功能微生物组成及其功能基因变化特征,研究微生物铁代谢对BSC演替的响应及调控。结果表明：真菌参与铁吸收和转运过程,古菌参与铁转运和贮存过程,细菌则在铁代谢吸收、转运和贮存过程中均起主要调控作用。门水平上,BSC铁代谢功能微生物组成变化对演替的响应不敏感,BSC铁代谢微生物主要为变形菌门（Proteobacteria）。BSC铁代谢功能基因多样性的显著提高和三类铁代谢过程基因信号强度达到最高水平需要经过61 a的演替。调控BSC铁吸收过程的主要功能基因为亚铁氧化酶编码基因iro;调控原核生物铁转运过程的主要功能基因,为羟基苯甲酰丝氨酸铁外膜转运体编码基因cirA和Fe（Ⅱ）转运蛋白编码基因feoB,真菌铁转运过程主要依靠含铁细胞转运体和铁氧化酶高亲和力的作用;调控铁贮存过程的主要功能基因为固定相类核蛋白编码基因dps。在BSC演替阶段末期,上述铁代谢功能基因强度的显著增加促进了微生物的铁代谢潜能。干旱、半干旱荒漠生态系统植被恢复过程中微生物铁代谢潜能的恢复需要较长时间。     

基于单历元方法研究汶川8.0级地震对中国大陆的同震变形影响

本文基于BERN5.0软件的动态计算功能,首先验证了GPS连续运行站观测数据单历元计算的可靠性,将其应用到汶川地震当天的观测数据,计算了全国29个连续运行站在地震前后30分钟的瞬时变化,获得了相应的同震变形,重点研究了泸州、西安、北京房山等站的变化情况,计算结果表明,在地震前后,各连续运行站监测到了明显的震间变形.     

基于单时相MODIS数据的决策树自动构建及分类研究

以甘肃省为试验区,利用单时相MODIS数据的光谱信息,使用最大似然法和基于See 5.0数据挖掘的决策树分类方法,进行了分类对比研究.分类结果表明,加入温度一植被角度TVA和温度-植被距离TVD两个指数后,低植被覆盖区的分类效果得到了改善;基于See 5.0数据挖掘的决策树方法能够快速地建立决策树,且能提高较难识别地物类型的分类精度.     

2006年甘肃文县5.0级地震灾害损失评估

2006年6月21日在甘肃省文县发生MS5.0地震,造成了建筑物破坏及人员伤亡。在震后开展的地震现场考察与震害评估工作中,将灾区分为2个评估子区,完成了29个点的震害抽样调查工作,根据地震灾害损失评估系统EDLES2.5的要求建立了有关数据库,做出了经济损失评估,并针对灾害特点给出了灾区恢复重建的建议。     

山西洪洞ML5.0地震前后临潼台流体异常特征

采用滤波、拟合、去周期、五日均值等方法,对临潼台水氡、水温、水溶气资料进行了分析处理,得到以下认识:用提取异常方法对原始曲线进行处理后,地震前兆异常更加明显与突出,这些异常均属于短期和临震前兆异常;临潼台流体对2003年山西洪洞ML5.0地震有明显反映,其原因一方面由于此次地震距临潼台较近,另一方面也反映了临潼台所处构造位置比较特殊,位于映震的灵敏位置。     

基于C5.0算法的胃癌生存预测模型研究

我国的胃癌发病率高,每年新增胃癌患者占全世界每年新增数量的42％,胃癌成为我国恶性肿瘤防控的重点.本文针对胃癌数据的特征,给出数据预处理和集成方法;采用C5.0分类算法,构建了胃癌生存预测模型,并首次采用美国癌症研究所的SEER数据库进行预测实验.实验结果表明：C5.0预测的精确度、特异性均高于BP-神经网络算法;胃癌患者的出生地点与最终的存活状态之间存在较强的相关性.该研究是数据挖掘技术在医学领域的一个实际应用,对胃癌的临床诊断具有一定的参考价值,可为医生制定合理的治疗和预防方案提供一定参考.     

Analysis of Anomalous Characteristics of Regional Crustal Deformation before the September 16th, 2019 Zhangye MS5.0 Earthquake, Gansu, China

To study the crustal movement in the vicinity of the epicenter before the Zhangye M_S5.0 earthquake in 2019, the characteristics of crustal deformation before the earthquake are discussed through the GPS velocity field analysis based on the CMONOC data observed from GPS. The baseline time series between two continuous GPS stations and the strain time series of an area among several stations are analyzed in the epicenter area. The resulting time series of baseline azimuth around the epicenter reflects that the energy of the fault in the northern margin of Qilian Mountain is accumulated continuously before 2017. Besides, the movement trend of azimuth slows down after 2017, indicating the stress accumulation on both sides of the seismogenic fault zone has reached a certain degree. The first shear strain and EW-direction linear strain in the epicentral area of the Zhangye M_S5.0 earthquake remain steady after 2017, and the surface strain rate decreases gradually after 2016. It is illustrated that there is an obvious deformation loss at the epicentral region three years before the earthquake, indicating that a certain degree of strain energy is accumulated in this area before the earthquake.