Pb同位素三维空间拓扑投影与化探评价

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。     

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Spatial and multivariate analysis of geochemical data from metavolcanic rocks in the Ben Nevis area, Ontario

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     

黄河流域上游降水时空结构特征

黄河兰州以上区域水资源量占黄河流域水资源的一半以上,研究黄河上游兰州以上区域降水时空结构变化具有重要意义。本文利用黄河兰州以上19个降水站点1959~1998年系列数据,采用EOF技术分析了黄河上游降水的时空结构特征与变化。结果表明：黄河上游兰州以上区域降水存在四种典型降水类型,即“全部一致型”、“南北型”、“东西型”和“相间复杂型”。但第一特征向量为主导,其时间变化系数与年降水量基本一致,说明黄河流域兰州以上降水主要受青藏高原大尺度气候影响,具有降水偏多（少）一致性特征。从时间尺度上降水有减少的趋势;并伴随3、6、和11年的周期变化,而且在1986和1991年发生突变。     

欧亚冬季雪盖异常及其与ENSO循环的关系

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。     

主成分分析法在林甸Ms5．1地震回顾性预测中的应用

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。     

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

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...     

Primary component analysis method and reduction of seismicity parameters

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…     

北太平洋500hpa候高度场的主成分分析

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。     

使用因子分析方法研究吉林前郭地震前的地震活动异常

本文用2006年吉林前郭MS5.0级地震前后震中附近的地震资料,选择反映地震活动时、空、强特征的地震频次N（ML≥3.0）、b值、η值、A（b）值、Mf值、Ac值、C值和D值8个参量进行因子分析。这些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。根据因子分析得到反映地震活动时、空、强特征的综合指标Wfa值,该指标在前郭MS5.0级地震前出现明显异常变化,表明综合指标Wfa值可以较好地反映地震活动的异常特征。