共查询到20条相似文献，搜索用时 15 毫秒
1.
Yongbo Gao Christoph Merz Gunnar Lischeid Michael Schneider 《Environmental Earth Sciences》2018,77(2):47
Like almost all fields of science, hydrology has benefited to a large extent from the tremendous improvements in scientific instruments that are able to collect long-time data series and an increase in available computational power and storage capabilities over the last decades. Many model applications and statistical analyses (e.g., extreme value analysis) are based on these time series. Consequently, the quality and the completeness of these time series are essential. Preprocessing of raw data sets by filling data gaps is thus a necessary procedure. Several interpolation techniques with different complexity are available ranging from rather simple to extremely challenging approaches. In this paper, various imputation methods available to the hydrological researchers are reviewed with regard to their suitability for filling gaps in the context of solving hydrological questions. The methodological approaches include arithmetic mean imputation, principal component analysis, regression-based methods and multiple imputation methods. In particular, autoregressive conditional heteroscedasticity (ARCH) models which originate from finance and econometrics will be discussed regarding their applicability to data series characterized by non-constant volatility and heteroscedasticity in hydrological contexts. The review shows that methodological advances driven by other fields of research bear relevance for a more intensive use of these methods in hydrology. Up to now, the hydrological community has paid little attention to the imputation ability of time series models in general and ARCH models in particular. 相似文献
2.
Helmut Mayer 《Mathematical Geology》1993,25(7):975-1001
The importance of time-series analysis in cyclic stratigraphy is evaluated by comparing three different methods (adaptive multiple taper spectral analysis, auto-/cross-correlation analysis, cova functions) applied to stratigraphic time series from the Early Cretaceous Cismon section in northern Italy. Carbonate content and magnetic susceptibility vary in a quasi-cyclic fashion in this pelagic limestone section and are almost perfectly negatively correlated. The spectral technique requires a high degree of preprocessing of the original data (interpolation and resampling at a regular interval, filtering, inversion) which introduces smoothing and rounding errors. The statistical correlation analysis also requires evenly and (for cross-correlation) correspondingly spaced series. The geostatistical cova functions (a generalization of the cross-variogram) prove to be the most versatile and robust of the methods compared. Cova functions can be calculated from unevenly and noncor-respondingly spaced time series without any preprocessing. This method also retains relatively more of the signal if noise and extreme outliers obscure the picture. The periodicities detected in the Cismon time series fall in the range of Milankovitch cycles. Cycle periods of 45 cm and 80 cm likely correspond to dominant precession and obliquity cycles. Due to the inaccuracy of the Cretaceous time scale periods cannot be matched exactly yet, but cycle ratios are close to expected ratios so that there is great potential for future cyclostratigraphic work to contribute to a substantial improvement of the geologic time scale. 相似文献
3.
涡动相关仪观测蒸散量的插补方法比较 总被引：5，自引：1，他引：4
涡动相关仪在长时间连续观测中,观测数据会有不同程度的缺失.应用6种不同的插补方法(平均昼夜变化法MDV,非线性回归方法NLR,动态线性回归方法DLR,查表法LUT,FAO-PM方法,HANTS方法)对北京密云站2007年涡动相关仪观测蒸散量数据进行了插补.结果表明:LUT方法在不同数据缺失时均得到较好结果(均方差小于8 W/m2);MDV和NLR方法更适合于短时间数据缺失的插补:DLR和FAO-PM方法在观测数据出现连续波动时插补结果较差.由LUT、DLR、NLR、HANTS、FAO-PM方法得到的年蒸散量分别为395.8 mm、409.9 mm、393.5 mm、390.7 mm、399.4 mm,差异在2.3～19.2 mm之间变化.对比分析了LUT方法得到的年蒸散量(潜热通量)与净辐射、降水量以及LAS观测潜热通量间的变化规律,表明插补结果合理. 相似文献
4.
Wavelet transforms have been used widely to analyse environmental data. These data typically comprise a series of measurements
taken at regular intervals in time or space. The analysis offers a decomposition of the data that distinguishes components
at different spatial scales but also, unlike Fourier analysis, can resolve local intermittent features. Most wavelet methods
require the data to be sampled at regular intervals and little attention has been paid to developing methods for data that
are not. In this paper, we derive a discrete Haar wavelet transform for irregularly sampled data and show how the resulting
wavelet coefficients can be used to estimate contributions of variance. We discuss the interpretation of these statistics
using data on apparent soil electrical conductivity of soil measured across a landscape as an example. 相似文献
5.
Some commonly used interpolation algorithms are analyzed briefly in this paper. Among all of the methods, biharmonic spline
interpolation, which is based on Green’s function and proposed by Sandwell, has become the mainstream method for its high
precision, simplicity and flexibility. However, the minimum curvature method has two flaws. First, it suffers from undesirable
oscillations between data points, which is solved by interpolation with splines in tension. Second, the computation time is
approximately proportional to the cube of the number of data constraints, making the method slow for situations with dense
data coverage. Focusing on the second problem, this paper introduces the moving surface spline interpolation method based
on Green’s function, and the interpolation error equations are deduced. Because the proposed method only chooses the nearest
data points by using the merge sort algorithm for interpolating, the computation time is greatly decreased. The optimal number
of the nearest points can be determined by using the interpolation error estimation equation. No matter how many data points
there are, this method can be implemented without difficulty. Examples show that the proposed method can obtain high interpolation
precision and high computation speed at the same time. 相似文献
6.
A comparative study for the estimation of geodetic point velocity by artificial neural networks 总被引：1，自引：0，他引：1
Space geodesy era provides velocity information which results in the positioning of geodetic points by considering the time evolution. The geodetic point positions on the Earth’s surface change over time due to plate tectonics, and these changes have to be accounted for geodetic purposes. The velocity field of geodetic network is determined from GPS sessions. Velocities of the new structured geodetic points within the geodetic network are estimated from this velocity field by the interpolation methods. In this study, the utility of Artificial Neural Networks (ANN) widely applied in diverse fields of science is investigated in order to estimate the geodetic point velocities. Back Propagation Artificial Neural Network (BPANN) and Radial Basis Function Neural Network (RBFNN) are used to estimate the geodetic point velocities. In order to evaluate the performance of ANNs, the velocities are also interpolated by Kriging (KRIG) method. The results are compared in terms of the root mean square error (RMSE) over five different geodetic networks. It was concluded that the estimation of geodetic point velocity by BPANN is more effective and accurate than by KRIG when the points to be estimated are more than the points known. 相似文献
7.
Nadav Sorek Eduardo Gildin Fani Boukouvala Burcu Beykal Christodoulos A. Floudas 《Computational Geosciences》2017,21(2):247-266
The objective of this paper is to introduce a novel paradigm to reduce the computational effort in waterflooding global optimization problems while realizing smooth well control trajectories amenable for practical deployments in the field. In order to overcome the problems of slow convergence and non-smooth impractical control strategies, often associated with gradient-free optimization (GFO) methods, we introduce a generalized approach which represent the controls by smooth polynomial approximations either by a polynomial function or by a piecewise polynomial interpolation, which we denote as function control method (FCM) and interpolation control method (ICM), respectively. Using these approaches, we aim to optimize the coefficients of the selected functions or the interpolation points in order to represent the well-control trajectories along a time horizon. Our results demonstrate significant computational savings, due to a substantial reduction in the number of control parameters, as we seek the optimal polynomial coefficients or the interpolation points to describe the control trajectories as opposed to directly searching for the optimal control values (bottom hole pressure) at each time interval. We demonstrate the efficiency of the method on two and three-dimensional models, where we found the optimal variables using a parallel dynamic-neighborhood particle swarm optimization (PSO). We compared our FCM-PSO and ICM-PSO to the traditional formulation solved by both gradient-free and gradient-based methods. In all comparisons, both FCM and ICM show very good to superior performances. 相似文献
8.
化学测量中不确定度的计算方法——不确定度连续传递模型计算示例 总被引：2，自引：0，他引：2
不确定度连续传递模型的基本步骤为：①对标准曲线的各点进行不确定度评定,给出各点的标准不确定度;②对标准曲线各点的响应值进行多次测定,得出其平均值和标准不确定度;③以这2个标准不确定度为权重进行拟合,得出双误差拟合方程和标准不确定度的计算公式;④计算标准曲线各点与其校准点的差值,并将其转换成标准不确定度;⑤将以上4项按不确定度传播规律计算总不确定度。实际测量时, ①、②、④步用插值法算得。通过一个实例比较了不同拟合方法间结果的差别,说明了运用X、Y的相对误差作为权重的直线拟和,再加上“不确定度连续传递模型”算得的测量不确定度更为合理。 相似文献
9.
不确定度连续传递模型的基本步骤为：①对标准曲线的各点进行不确定度评定,给出各点的标准不确定度;②对标准曲线各点的响应值进行多次测定,得出其平均值和标准不确定度;③以这2个标准不确定度为权重进行拟合,得出双误差拟合方程和标准不确定度的计算公式;④计算标准曲线各点与其校准点的差值,并将其转换成标准不确定度;⑤将以上4项按不确定度传播规律计算总不确定度。实际测量时, ①、②、④步用插值法算得。通过一个实例比较了不同拟合方法间结果的差别,说明了运用X、Y的相对误差作为权重的直线拟和,再加上“不确定度连续传递模型”算得的测量不确定度更为合理。 相似文献
10.
Kriging插值方法在地层模型生成中的应用 总被引：9，自引：1，他引：8
为了建立三维数字地层,采用了一种适合城市工程地质和岩土工程特点的地层数据模型-基于钻孔信息的3棱柱模型。由于钻孔之间的距离稀疏程度、方向、数据值存在差异,钻孔以外未知的地质特性需要插值和推断,传统的数理统计方法无法很好地解决空间样本点的选取、空间估值和2组以上空间数据的关系等问题。借鉴地质统计学的Kriging方法给出一种距离加权插值算法,即先根据空间数据得到统计特征,再根据统计特征进行插值。通过对地层模型插值结果的观察,得出该算法可以获得良好的插值效果。 相似文献
11.
Mingyue Lu Min Chen Xinhao Wang Manzhu Yu Yongyao Jiang Chaowei Yang 《Environmental Earth Sciences》2018,77(24):804
Weather radar data, which have obvious spatial characteristics, represent an important and essential data source for weather identification and prediction, and the multi-dimensional visualization and analysis of such data in a three-dimensional (3D) environment are important strategies for meteorological assessments of potentially disastrous weather. The previous studies have generally used regular 3D raster grids as a basic structure to represent radar data and reconstruct convective clouds. However, conducting weather radar data analyses based on regular 3D raster grids is time-consuming and inefficient, because such analyses involve considerable amounts of tedious data interpolation, and they cannot be used to address real-time situations or provide rapid-response solutions. Therefore, a new 3D modelling strategy that can be used to efficiently represent and analyse radar data is proposed in this article. According to the mode by which the radar data are obtained, the proposed 3D modelling strategy organizes the radar data using logical objects entitled radar-point, radar-line, radar-sector, and radar-cluster objects. In these logical objects, the radar point is the basic object that carries the real radar data unit detected from the radar scan, and the radar-line, radar-sector, and radar-cluster objects organize the radar-point collection in different spatial levels that are consistent with the intrinsic spatial structure of the radar scan. Radar points can be regarded as spatial points, and their spatial structure can support logical objects; thus, the radar points can be flexibly connected to construct continuous surface data with quads and volume data with hexahedron cells without additional tedious data interpolation. This model can be used to conduct corresponding operations, such as extracting an isosurface with the marching cube method and a radar profile with a designed sectioning algorithm to represent the outer and inner structure of a convective cloud. Finally, a case study is provided to verify that the proposed 3D modelling strategy has a better performance in radar data analysis and can intuitively and effectively represent the 3D structure of convective clouds. 相似文献
12.
Traditional interpolation procedures used for processing geochemical data treat the data as a continuous smooth surface. In this paper, we proposed a fractal spatial interpolatory procedure based on the concept of the fractional delta variance. The method is suitable for processing the geochemical data that are measured at irregularly spaced discrete points, without resort to gridding procedures. The value at each interpolatory point is a function of the fractal disturbance that is related to the fractal dimension determined from the original data set, thus enhancing reconstruction of the natural spatial distribution of element concentration. The proposed procedure has been applied to the copper geochemical data measured from irregularly-spaced floodplain sediment samples in China. We compared geochemical maps created using different interpolatory procedures, including the new fractal method, the Kriging, and the weighted average, against the actual spatial distribution of copper mineral deposits in China, and found that the new fractal method detected more of known Cu-deposits from the test area than the other two methods. 相似文献
13.
复杂地层建模与三维可视化 总被引：1，自引：0，他引：1
提出了一种新的复杂地层建模方法。该方法先将离散的钻孔数据点分类,而后将不同类的离散数据点用径向基函数进行拟合;所生成的拟合曲面相交、裁剪得到地层的空间范围;由离散的数据点以及拟合插值点生成地层交界面格网,再经过计算机图形处理生成地层模型的三维图形。利用该方法对复杂地层建模,自动化程度较高、效果较好。 相似文献
14.
Mohammad Arab Amiri Yazdan Amerian Mohammad Saadi Mesgari 《Arabian Journal of Geosciences》2016,9(5):421
This paper aims to provide a spatial and temporal analysis to prediction of monthly precipitation data which are measured at irregularly spaced synoptic stations at discrete time points. In the present study, the rainfall data were used which were observed at four stations over the Qara-Qum catchment, located in the northeast of Iran. Several models can be used to spatially and temporally predict the precipitation data. For temporal analysis, the wavelet transform with artificial neural network (WTANN) framework combines with the wavelet transform, and an artificial neural network (ANN) is used to analyze the nonstationary precipitation time-series. The time series of dew point, temperature, and wind speed are also considered as ancillary variables in temporal prediction. Furthermore, an artificial neural network model was used for comparing the results of the WTANN model. Therefore, four models were developed, including WTANN and ANN with and without ancillary data. Several statistical methods were used for comparing the results of the temporal analysis. It was evident that at three of the four stations, the WTANN models were more effective than the ANN models, and only at one station, the ANN model with ancillary data had better performance than the WTANN model without ancillary data. The values of correlation coefficient and RMSE for WTANN model with ancillary data for the validation period at Mashhad station which showed the best results were equal to 0.787 and 13.525 mm, respectively. Finally, an artificial neural network model was used as an alternative interpolating technique for spatial analysis. 相似文献
15.
Pankaj K. Mishra Sankar K. Nath Mrinal K. Sen Gregory E. Fasshauer 《Computational Geosciences》2018,22(5):1203-1218
Scattered data interpolation schemes using kriging and radial basis functions (RBFs) have the advantage of being meshless and dimensional independent; however, for the datasets having insufficient observations, RBFs have the advantage over geostatistical methods as the latter requires variogram study and statistical expertise. Moreover, RBFs can be used for scattered data interpolation with very good convergence, which makes them desirable for shape function interpolation in meshless methods for numerical solution of partial differential equations. For interpolation of large datasets, however, RBFs in their usual form, lead to solving an ill-conditioned system of equations, for which, a small error in the data can cause a significantly large error in the interpolated solution. In order to reduce this limitation, we propose a hybrid kernel by using the conventional Gaussian and a shape parameter independent cubic kernel. Global particle swarm optimization method has been used to analyze the optimal values of the shape parameter as well as the weight coefficients controlling the Gaussian and the cubic part in the hybridization. Through a series of numerical tests, we demonstrate that such hybridization stabilizes the interpolation scheme by yielding a far superior implementation compared to those obtained by using only the Gaussian or cubic kernels. The proposed kernel maintains the accuracy and stability at small shape parameter as well as relatively large degrees of freedom, which exhibit its potential for scattered data interpolation and intrigues its application in global as well as local meshless methods for numerical solution of PDEs. 相似文献
16.
多维分形克里格方法 总被引：9，自引：0，他引：9
时间序列与空间场信号往往是非规则分布的，经常需要将非规则分布的时空信号插值为规则分布的信号或估计某些未知点的值。如油气田、煤田以及金属矿山储量估算，工程地质参数估计，病虫害区域分布调查等都要求根据少量不规则数据点进行插值估算。估值方法中应用最为广泛的地质统计学方法（或(Krige)克里格方法）是一种低通滤波器，无法重建原始信号中的高频、局部与弱信号。开发的多维分形克里格方法可以将不规则分布的时间—空间（时空）信号插值为规则分布的信号；可以提取时空信号中高频、局部与弱信号，估计过程参数可以作为特征参数用于模式识别。利用褶积滤波理论定量导出了地质统计学的低通滤波特性，它在插值过程中丢失了高频、局部和弱信号。在定义了时空信号的度量尺度与测度后，实现了多维分形插值，多维分形插值保留了系统中更多的高频信息。将克里格方法与多维分形方法有机的结合起来产生了多维分形克里格方法，它具有克里格方法和多维分形插值的共同优点。用大洋钻探(ODP)184航次1143A孔的岩芯密度分析进行了插值试验，对比了插值结果及其功率谱。多维分形克里格插值比克里格插值、多维分形插值更为接近已知点值并保留更多的高频信息。还定量分析、对比了影响多维分形克里格插值的因素、厘清了估值问题中固有的测不准关系。
另外，多维分形克里格插值过程得到的局部奇异性、相关性和回归方差能有效地刻划高频、局部与弱信号。这样，多维分形克里格插值过程可以用于提取（非规则或规则网格）时空信号中的局部、高频与弱信号，用于信息提取、模式识别、找矿预测与信号增强等领域。 相似文献
17.
广义回归神经网络预测加筋土支挡结构高度 总被引：9，自引：3，他引：9
土工合成材料加筋支挡结构（Geosythetics-Reinforced Retaining Wall, 简称GRW）设计方法主要是建立在似粘聚力理论基础之上的半经验设计法。由于土性及加筋机理的复杂性，常常要对它们进行人为假定，导致计算结果差强人意。神经网络方法与传统方法的不同之处在于不需要主观假定，而是模拟人脑思维，通过数据样本的学习来获得预测结果。引入神经网络技术来预测加筋土支挡结构的设计高度是一种新尝试。由于本问题具有样本容量非常有限、影响因素复杂多样的特点。因此，采用适用于稀土样本数据的广义回归网络（General Regression Neural Network)来预测加筋土支挡结构设计高度。基于MATLAB神经网络工具箱及文献[1]的挡墙离心模型试验结果，建立了一个可用于加筋支挡结构设计高度预测的GRNN网络。通过对足尺试验，实际工程及模型试验结果的检验，表明网络的学习是成功的，具有一定指导意义。 相似文献
18.
19.
对断裂数据化处理,得到断裂控制点。以断裂控制点为约束,对断裂进行点插值,以单个统计单元为视窗,统计落入不同栅格内的插值点数目,进而求得插值点落入不同栅格的概率,对变量数据拟合,得到断裂信息维以及相关系数。将该思路应用在金湖凹陷阜二段断裂分形评价中,分别计算了断裂长度信息维、面积信息维。结果表明,90%以上的统计单元相关系数0.9,断裂发育区具有较高的自相似性,断裂总体分形特征曲线的相关系数0.999。金湖凹陷断裂的计算表明,该思路是测量断裂信息维的有效方法,能够提高工作效率,具有较好的应用前景。 相似文献
20.
涡动相关仪在长时间连续观测中,观测数据会有不同程度的缺失。应用6种不同的插补方法（平均昼夜变化法MDV,非线性回归方法NLR,动态线性回归方法DLR,查表法LUT,FAO PM方法,HANTS方法）对北京密云站2007年涡动相关仪观测蒸散量数据进行了插补。结果表明： LUT方法在不同数据缺失时均得到较好结果（均方差小于8 W/m2）;MDV和NLR方法更适合于短时间数据缺失的插补; DLR和FAO PM方法在观测数据出现连续波动时插补结果较差。由LUT、DLR、NLR、HANTS、FAO PM方法得到的年蒸散量分别为395.8 mm、409.9 mm、393.5 mm、390.7 mm、399.4 mm,差异在2.3~19.2 mm之间变化。对比分析了LUT方法得到的年蒸散量（潜热通量）与净辐射、降水量以及LAS观测潜热通量间的变化规律,表明插补结果合理。 相似文献