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131.
云南大红山铁矿床三维数学模型探讨 总被引:6,自引:0,他引:6
为实现矿山的生产动态管理与矿床的三维可视化,应用地质统计学的理论和方法,尤其是应用能够反映区域化变量特征的变异函数,借助计算机和Micromine软件包,建立了大红山铁矿床的三维矿床数学模型。结果表明,该模型可以使矿山很清楚地了解矿体的形态、产状和化学组分分布特征等。此外,通过Kriging估值计算的储量与用传统方法计算的储量很接近。 相似文献
132.
含水层渗透性空间分布的指示克立格估值 总被引:3,自引:0,他引:3
详细介绍了指示克立格估值计算的理论和方法。以指示变异函数为基本工具分析了华北某地区第四系含水层渗透性空间分布的结构特征,结果表明该地区含水层渗透性存在明显的各向异性特征。水平方向上,X轴方向的相关性较Y轴方向的好,Z轴的相关性最差。用指示克立格法对未采样点处进行估值,估值结果显示含水层渗透性由山前向滨海逐渐变低,在垂直方向上,渗透性变化不明显,浅部比深部略好;同时给出了估计精度,并认为对估计精度不高的区域可通过增加适当的工程加以控制。最后用交叉验证法对估值结果进行了检验,证明建立的指示变异函数模型合理且估值效果较好。这一实际应用表明指示克立格法可以很好地描述第四系含水层渗透性的空间分布规律。 相似文献
133.
As an application, we demonstrate a proposed variogram modeling scheme using a spatial data set. Because the scheme relies on a procedure for simultaneously diagonalizing several matrices, we briefly describe the FG and least-squares algorithms. The model obtained by our scheme is used to cokrige the data. In addition, the proposed scheme is compared to more traditional methods. 相似文献
134.
Spatial orthogonality of the principal components computed from coregionalized variables 总被引:6,自引:0,他引:6
P. Goovaerts 《Mathematical Geology》1993,25(3):281-302
Within the frame of the linear model of coregionalization, this paper sets up equations relating the variogram matrix of the principal components extracted from the variance-covariance matrix to the diagonal variogram matrices of the regionalized factors. The spatial orthogonality of the principal components is investigated in three situations: the intrinsic correlation, two basic structures with independent nugget components, three basic structures with independent nugget components and uncorrelated subsets of variables. Two examples point out that the correlation between the principal components may be nonnegligible at short distances, especially if the correlation structure changes according to the spatial scale considered. For one of the two case studies, an orthogonal varimax rotation of the first principal components is found to greatly reduce the spatial correlation between some of them. 相似文献
135.
The Necessity of a Multiple-Point Prior Model 总被引:9,自引:0,他引:9
Any interpolation, any hand contouring or digital drawing of a map or a numerical model necessarily calls for a prior model
of the multiple-point statistics that link together the data to the unsampled nodes, then these unsampled nodes together.
That prior model can be implicit, poorly defined as in hand contouring; it can be explicit through an algorithm as in digital
mapping. The multiple-point statistics involved go well beyond single-point histogram and two-point covariance models; the
challenge is to define algorithms that can control more of such statistics, particularly those that impact most the utilization
of the resulting maps beyond their visual appearance. The newly introduced multiple-point simulation (mps) algorithms borrow
the high order statistics from a visually and statistically explicit model, a training image. It is shown that mps can simulate
realizations with high entropy character as well as traditional Gaussian-based algorithms, while offering the flexibility
of considering alternative training images with various levels of low entropy (organized) structures. The impact on flow performance
(spatial connectivity) of choosing a wrong training image among many sharing the same histogram and variogram is demonstrated. 相似文献
136.
137.
Xavier Emery 《Stochastic Environmental Research and Risk Assessment (SERRA)》2007,21(4):391-403
In the analysis of regionalized data, irregular sampling patterns are often responsible for large deviations (fluctuations)
between the theoretical and sample semi-variograms. This article proposes a new semi-variogram estimator that is unbiased
irrespective of the actual multivariate distribution of the data (provided an assumption of stationarity) and has the minimal
variance under a given multivariate distribution model. Such an estimator considerably reduces fluctuations in the sample
semi-variogram when the data are strongly correlated and clustered in space, and proves to be robust to a misspecification
of the multivariate distribution model. The traditional and proposed semi-variogram estimators are compared through an application
to a pollution dataset. 相似文献
138.
顾及距离值的随机误差,提出用加权总体最小二乘回归法估计变异函数模型参数。通过协方差传播律发现,分组后的变异函数值和距离值是不等精度的。给出距离值的定权方法,结合熵权法和点对数法迭代解算模型参数。以幂函数模型为例,模拟数据和实测数据的结果表明,加权总体最小二乘回归法更加合理,参数的估计精度也更高。 相似文献
139.
变异函数是地统计学中区域化变量空间结构分析和空间局部插值的主要分析工具.理论变异函数模型的获取是地质统计学中的基础性工作,它是了解区域化变量的变异特征、进一步对地质统计学计算的必要环节.针对现有的理论变异函数的拟合方法,如人工拟合法、线性规划拟合法、加权多项式拟合法、目标规划拟合法等的不足之处,充分利用粒子群优化算法在求解非线性优化问题时具有的全局寻优的特点,提出基于粒子群优化的理论变异函数拟合方法.在实例应用中,分别利用粒子群优化算法和加权多项式拟合方法进行理论变异函数拟合,交叉验证结果表明粒子群优化算法预测精度较高,具有较强的稳健性. 相似文献
140.
???????????????????????????????????У???????????????????????и????????????????????????μ???????????顣????????????÷????????????????????????????????????????????????????????????Ч??????? 相似文献