欧亚冬季雪盖异常及其与ENSO循环的关系     

王静  孙照渤 《南京气象学院学报》2003,26(1):38-46

利用 NOAA- NESDIS提供的 1 973— 2 0 0 0年北半球雪盖面积资料 ,研究了欧亚冬季雪盖的时空特征 ,发现欧亚大陆中高纬地区积雪有明显的整体性分布特征 ,而50°N以南的冬季积雪随纬度的变率较大 ;欧亚大陆中高纬地区冬季积雪呈东西反位相分布。利用小波分析发现 ,冬季欧亚积雪具有显著的 3～ 4 a周期。最后指出 ,欧亚积雪异常引起的下垫面热力异常可能为次年 El Nino事件的爆发提供触发条件。  相似文献   

Pb同位素三维空间拓扑投影与化探评价     

常向阳  朱炳泉 《地球学报》1997,18(Z1):182-184

通过对数据集合的拓扑学分析，获得了Pb同位素三维空间拓扑投影特征值V1和V2。运用特征值可以定量地预测隐伏铜金矿床的埋藏深度和隐伏矿量，是隐伏矿预测评价的新方法，开创了同位素化探的新领域。  相似文献   

Primary component analysis method and reduction of seismicity parameters     

王炜  马钦忠  林命周  吴耿锋  吴绍春 《地震学报(英文版)》2005,18(5):562-571

Introduction Data mining (SHAO and YU, 2003) is a new kind of technique developed with database and artificial intelligence in recent years, which processes the data in the database to abstract the im- plied and pre-unknown, but potentially useful information and knowledge from large amounts of incomplete, noisy, blurring and stochastic data. For data mining, data purging is an important link beforehand that includes eliminating noise, making up lost domain, and deleting ineffective data, as…  相似文献   

Spatial and multivariate analysis of geochemical data from metavolcanic rocks in the Ben Nevis area, Ontario   总被引：4，自引：0，他引：4  

E. C. Grunsky  F. P. Agterberg 《Mathematical Geology》1988,20(7):825-861

A study of the lithogeochemistry of metavolcanics in the Ben Nevis area of Ontario, Canada has shown that factor analysis methods can distinguish lithogeochemical trends related to different geological processes, most notably, the principal compositional variation related to the volcanic stratigraphy and zones of carbonate alteration associated with the presence of sulphides and gold. Auto- and cross-correlation functions have been estimated for the two-dimensional distribution of various elements in the area. These functions allow computation of spatial factors in which patterns of multivariate relationships are dependent upon the spatial auto- and cross-correlation of the components. Because of the anisotropy of primary compositions of the volcanics, some spatial factor patterns are difficult to interpret. Isotropically distributed variables such as CO ₂ are delineated clearly in spatial factor maps. For anisotropically distributed variables (SiO ₂ ), as the neighborhood becomes smaller, the spacial factor maps becomes better. Interpretation of spatial factors requires computation of the corresponding amplitude vectors from the eigenvalue solution. This vector reflects relative amplitudes by which the variables follow the spatial factors. Instability of some eigenvalue solutions requires that caution be used in interpreting the resulting factor patterns. A measure of the predictive power of the spatial factors can be determined from autocorrelation coefficients and squared multiple correlation coefficients that indicate which variables are significant in any given factor. The spatial factor approach utilizes spatial relationships of variables in conjunction with systematic variation of variables representing geological processes. This approach can yield potential exploration targets based on the spatial continuity of alteration haloes that reflect mineralization.List of symbols c _i Scalar factor that minimizes the discrepancy between andU _i - D Radius of circular neighborhood used for estimating auto- and cross-correlation coefficients - d Distance for which transition matrixU is estimated - d _ij Distance between observed valuesi andj - E Expected value - E _i Row vector of residuals in the standardized model - F(d _ij) Quadratic function of distanced _ij F(d _ij)=a+bd _ij+cd _ij ² - L Diagonal matrix of the eigenvalues ofU - _i Eigenvalue of the matrixU;ith diagonal element ofL - N Number of observations - p Number of variables - Q Total predictive power ofU - R Correlation matrix of the variables - R _0j Variance-covariance signal matrix of the standardized variables at origin;j is the index related tod andD (e.g.,j=1 ford=500 m,D=1000 m) - R _1j Matrix of auto- and cross-correlation coefficients evaluated at a given distance within the neighborhood - R _m ² Multiple correlation coefficient squared for themth variable - S _i Column vectori of the signal values - s _k ² Residual variance for variablek - T _i Amplitude vector corresponding toV _i;ith row ofT=V ^–1 - T Total variation in the system - U Nonsymmetric transition matrix formed by post-multiplyingR ₀₁ ^–1 byR _ij - U _i Componenti of the matrixU, corresponding to theith eigenvectorV _i;U _i= _iV_iT_i - U* _i ComponentU _i multiplied byc _i - U _ij Sum of componentsU _i+U _j - V _i Eigenvector of the matrixU;ith column ofV withUV=VL - w Weighting factor; equal to the ratio of two eigenvalues - X _i Random variable at pointi - x _i Value of random variable at pointi - y _i Residual ofx _i - Z _i Row vectori for the standardized variables - z _i Standardized value of variable  相似文献   

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陈兴权  王解先 《大地测量与地球动力学》2008,28(4):111-114

????????????????????????????Σ?????????????????????????????????趨???????????м???????е???????????????????ó?????????????????????????????????????????????????????????????????????????????淽??????????????????????????????????????????????????????????????????????????????淽???????????????????????????????????÷??????????Ч???  相似文献   

北太平洋500hpa候高度场的主成分分析     

胡基福  常美桂  由保传 《中国海洋大学学报(自然科学版)》1989,(2)

对太平洋500hPa候高度场和距平场进行了主成分分析,得出反映500hPa候高度特征的典型场。指出候高度场的第1特征向量的空间型是季节变化的主要型,它可解释总方差的74.5％,候高度场的其余特征向量与距平场的特征向量是按顺序的对应相似。这些典型场可以很好地描述北太平洋的大气环流特征。距平场的第1特征向量空间型清楚地反映了与厄尔·尼诺现象有关的环流型。  相似文献   

基于大型科研基础设施共享的区域创新网络研究——以山东省为例   总被引：2，自引：1，他引：1  

饶悦  沈丽珍  汪侠 《地理研究》2021,40(6):1840-1856

在产业革命和科技革命的背景下,创新在区域发展中发挥着越来越重要的作用,网络化创新模式成为当下创新的主流模式之一。基于创新网络视角,利用大型科研仪器共享大数据,对山东省创新网络的空间特征和主体特征进行分析,研究发现：山东省创新网络在形态上呈现出以济南为创新核心辐射带动济宁和淄博等周边边缘城市发展,同时形成东部青岛、威海和烟台作为创新次级核心集中连片发展的空间格局。然而,创新网络的形态核心节点与功能核心节点存在错位,从网络关联的角度出发,山东省区域创新网络节点存在核心、次核心、地方核心、外围4个层级,济南、济宁、淄博、潍坊中心地位明显,并且各级节点数量规模呈现金字塔格局,等级结构完善。网络联系强度最大的主要是济南市向周边辐射的联系,区域政产学研协同创新体系基本确立,存在综合创新模式、异质创新模式、根植创新模式和孤立创新模式四种创新网络模式。通过QAP模型分析表明,行政、交通等因素使得创新合作更倾向于发生在与省会城市之间以及地理接壤、交通条件优越的城市之间。最后,基于研究基础,对山东省创新网络优化、大型科研仪器共享、区域产业发展等提出发展建议。  相似文献   

中国省际人口迁移短期预测分析     

李建学  蒲英霞  刘大伟 《地理与地理信息科学》2021,37(2):54-62

人口迁移是一个时空路径依赖过程,同时受迁移存量和周边迁移状况影响。当前人口迁移预测大多建立在时间序列模型之上,重点考虑迁移流在时间维度上的联系,忽视了其中的时空关联。该文将特征向量时空滤波方法与普通泊松模型相结合,考虑迁移流中可能存在的时空滞后和同期两种结构,对1985-2015年不同时段的中国省际人口迁移流数据进行建模和估计,并利用拟合程度较优的模型预测2015-2025年省际人口迁移的发展趋势。结果表明:1)特征向量时空滞后和同期滤波泊松模型均能较好地模拟研究时段省际人口迁移过程,自1985年以来我国省际人口迁移流不仅受迁出地和迁入地经济、社会等因素影响,也与过去迁移存量及周边迁移流密切相关;2)区域人口规模和GDP对迁移流的“推—拉”作用符合预期,地区人口规模较高和经济发展水平较低会促进人口外迁,反之则有利于吸引外来人口;3)与特征向量时空滞后滤波泊松模型相比,时空同期模型更便于捕捉省际人口迁移过程中的时空路径依赖特性,意味着当前人口迁移流的发展更易受到同时期周边迁移流的影响,表现出明显的羊群效应;4)预计2015-2025年我国省际迁移总量持续增加,呈现更集聚的空间模式,高迁入与高迁出区域在空间上相连,形成一条南北贯通的“高密度迁移地带”。将特征向量时空滤波模型拓展到人口迁移这一空间相互作用领域,可为当前构建更加完善的要素市场化配置体制机制等提供科学参考。  相似文献   

The spatial patterns and determinants of internal migration of older adults in China from 1995 to 2015     

LIU Ye  HUANG Cuiying  WU Rongwei  PAN Zehan  GU Hengyu 《地理学报(英文版)》2022,32(12):2541-2559

Although China was one of the countries with the fastest-growing aging population in the world, limited scholarly attention has been paid to migration among older adults in China. The full picture of their migration in the entire country over time remains unknown. This study examines the spatial patterns of older interprovincial migration flows and their drivers in China over the period 1995 to 2015, using four waves of census data and intercensal population sample survey data. Results from eigenvector spatial filtering negative binomial regressions indicate that older adults tend to migrate away from low cost-of-living rural areas to high cost-of-living urban and rural areas, moving away from areas with extreme temperature differences. The location of their grandchildren is among the most important attractions. Our findings suggest that family-oriented migration is more common than amenity-led migration among retired Chinese older adults, and the cost-of-living is an indicator of economic opportunities for adult children and the quality of senior care services.  相似文献   

主成分分析法在林甸Ms5．1地震回顾性预测中的应用   总被引：3，自引：1，他引：2  

李永振 《东北地震研究》2008,24(2):29-34

用2005年林甸Ms5．1级地震前后震中附近的地震资料,选择与地震强度有关的3级以上地震频次N、b值、Mf值、C值、和Ac值等6个参量进行主成分分析,实现对上述参量的有效约简。这6个参量之间有一定的相关性,各参量在不同时段的变化各有所异,预报效果并不理想。但是根据主成分分析可以得到反映地震强度的综合指标W,发现该指标在震源区附近出现明显的异常变化,震后异常恢复。表明综合指标W可以较好的反映地震活动的异常特征。  相似文献