368 resultados para KRIGING


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利用地统计学和地理信息系统相结合的方法研究了沈阳市郊耕地1991个样本0~20cm耕层土壤交换性铁含量的空间异质性特征,绘制了交换性铁含量的空间分布图。结果表明:土壤交换性铁含量基本符合正态分布,变异函数的最佳理论模型为球状模型,交换性铁含量具有中等的空间相关性(C0与C0+C比值为41.3%,空间自相关距离为34.9km),Kriging内插图显示出交换性铁具有较强的空间异质性,其空间异质性主要受成土母质、成土过程和土壤类型等结构性因子的影响。

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利用地统计学和地理信息系统相结合的方法,研究了沈阳市苏家屯区耕地土壤(0~20 cm)有机质、速效氮、速效磷、速效钾含量的空间变异性特征.结果表明,各变量符合正态分布或经对数转换后符合正态分布,最佳的变异函数理论模型均为球状模型.有机质具有较强的空间相关性(C0与C0+C比值为24.11%),速效氮、速效磷、速效钾具有中度的空间相关性(C0与C0+C比值分别为29.53%、60.77%、58.82%).各变量的空间自相关距离分别为26.051、28.293、15.132和23.813 km.有机质和速效氮的空间变异主要受结构性因子(如成土因子)的影响,速效磷和速效钾主要受随机性因子(如施肥)的影响.Kriging插值绘制出的养分含量空问分布图显示了养分的空间分布格局,它将有助于进一步监测养分动态,为农业和环境管理提供数字地图支持.

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结合地理信息系统,运用地统计学方法研究石羊河下游民勤绿洲近15年来的地下水矿化度的时空变异规律及其与土地利用变化的关系。结果表明:(1)在1987年和2001年的两个时期地下水矿化度的实验变异函数值与理论变异函数拟合较好,F检验达到极显著水平;(2)地下水矿化度在4km以下小尺度上的随机变异SHR特别小,而在4~40km的中尺度上的结构性变异SHA达99.9%,可以认为研究区域内地下水矿化度在整个尺度上具有恒定的变异;(3)Kriging插值及其与同期的绿洲景观类型图进行叠加运算表明,在变化趋势上,除坝区东南部略有下降外,整个绿洲地下水矿化度都增大,北部湖区最显著;在变化面积上,地下水矿化度在3.0g/L以下的面积从1987年的75.26%降到了2001年的58.54%;而其>4.5g/L的绿洲主要集中在湖区。地下水矿化度较低区域的耕地面积减少,而地下水矿化度3.0g/L以上的耕地面积从7.03%增加到了14.32%,特别是湖区,地下水的矿化已严重威胁到了耕地的存在。

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以辽宁昌图烟区为例,采用GIS和地统计学相结合的方法,研究了县级区域植烟土壤有效态微量元素的空间变异及分布特征。结果表明:土壤有效态Fe、Mn、Cu、Zn、B、Mo含量的空间变异函数分别为高斯、高斯、球状、指数、指数、指数模型。其中,有效态Cu、Zn、B具有中等的空间相关性,其变异受母质、地形、土壤类型等结构因素和施肥、管理水平等随机因素的共同影响;有效态Fe、Mn、Mo的空间相关性微弱,其变异受随机因素影响较大。点克里格(Kriging)法插值图显示,Fe、Mn、Cu、Zn、B、Mo有效含量均总体呈现南高北低的分布趋势,其中Cu、Zn、B的分布格局相对更加复杂,在北部烟区表现为从西南向东北逐渐增加,在南部烟区表现为自中偏北部向四周逐渐降低。

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In addition to classical methods, namely kriging, Inverse Distance Weighting (IDW) and splines, which have been frequently used for interpolating the spatial patterns of soil properties, a relatively more accurate surface modelling technique is being developed in recent years, namely high accuracy surface modelling (HASM). It has been used in the numerical tests, DEM construction and the interpolation of climate and ecosystem changes. In this paper, HASM was applied to interpolate soil pH for assessing its feasibility of soil property interpolation in a red soil region of Jiangxi Province, China. Soil pH was measured on 150 samples of topsoil (0-20 cm) for the interpolation and comparing the performance of HASM, kriging. IDW and splines. The mean errors (MEs) of interpolations indicate little bias of interpolation for soil pH by the four techniques. HASM has less mean absolute error (MAE) and root mean square error (RMSE) than kriging, IDW and splines. HASM is still the most accurate one when we use the mean rank and the standard deviation of the ranks to avoid the outlier effects in assessing the prediction performance of the four methods. Therefore, HASM can be considered as an alternative and accurate method for interpolating soil properties. Further researches of HASM are needed to combine HASM with ancillary variables to improve the interpolation performance and develop a user-friendly algorithm that can be implemented in a GIS package. (C) 2009 Elsevier B.V. All rights reserved.

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Mapping the spatial distribution of contaminants in soils is the basis of pollution evaluation and risk control. Interpolation methods are extensively applied in the mapping processes to estimate the heavy metal concentrations at unsampled sites. The performances of interpolation methods (inverse distance weighting, local polynomial, ordinary kriging and radial basis functions) were assessed and compared using the root mean square error for cross validation. The results indicated that all interpolation methods provided a high prediction accuracy of the mean concentration of soil heavy metals. However, the classic method based on percentages of polluted samples, gave a pollution area 23.54-41.92% larger than that estimated by interpolation methods. The difference in contaminated area estimation among the four methods reached 6.14%. According to the interpolation results, the spatial uncertainty of polluted areas was mainly located in three types of region: (a) the local maxima concentration region surrounded by low concentration (clean) sites, (b) the local minima concentration region surrounded with highly polluted samples; and (c) the boundaries of the contaminated areas. (C) 2010 Elsevier Ltd. All rights reserved.

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The density and distribution of spatial samples heavily affect the precision and reliability of estimated population attributes. An optimization method based on Mean of Surface with Nonhomogeneity (MSN) theory has been developed into a computer package with the purpose of improving accuracy in the global estimation of some spatial properties, given a spatial sample distributed over a heterogeneous surface; and in return, for a given variance of estimation, the program can export both the optimal number of sample units needed and their appropriate distribution within a specified research area. (C) 2010 Elsevier Ltd. All rights reserved.

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激光焊接技术是现代焊接技术的重要组成部分之一,在板材深加工产业中占有重要地位。激光拼焊技术具有高效率、高速度、高精度、强适应性等特点,被广泛应用于汽车、造船、航天等领域。激光拼焊定位、夹紧机构是激光拼焊装备的核心技术之一。目前国外已经研制出高性能激光拼焊装备,国内仍处在实验研发阶段。因此,对激光拼焊定位、夹紧机构展开研究,对实现激光拼焊装备的发展具有重要意义。本文以中国科学院知识创新工程方向性项目“全自动激光拼焊成套装备关键技术研究与示范应用”为课题背景,结合项目实际开发中的具体要求,以激光拼焊生产线核心技术之一的定位、夹紧机构为研究对象,在定位、夹紧机构的创新设计及综合性能评价、焊缝碾压精密预成型原理与实现技术、碾压机构优化方法以及定位机构误差补偿方法等方面开展了深入研究,为激光拼焊装备研制提供理论和技术支持。本文首先对研究激光拼焊定位、夹紧机构所需的一些基本理论进行了综述。在此基础上系统的研究了激光拼焊定位、夹紧机构设计方法及性能评价模型、基于多体系误差建模方法、焊缝碾压精密预成型、基于Kriging模型的碾压机构优化设计方法等。这些方法对激光拼焊定位、夹紧机构设计具有指导意义。以沈阳自动化研究所研制的全自动激光拼焊生产线为背景,依据定位、夹紧机构性能评价模型分析了该生产线定位、夹紧机构设计原理及存在的问题。为了解决这些问题,采取了机构优化及改进、压紧力优化、过盈量作用机制、多组焊等措施。实际试验证明这些措施在一定程度上提高了定位、夹紧机构的性能,但是由于定位、夹紧机构自身结构特点,无法解决非线性定位误差和长焊缝料片的定位等问题。针对所研制的激光拼焊焊定位、夹紧机构的不足,结合国外相关先进技术,提出了一种新型激光拼焊定位、夹紧机构,对其结构和原理进行介绍,并建立了其参数化三维模型。为了保证料片的准连续传输,采用了传输带和辊子的方式传输板材;设计了水平方向成α角,竖直方向共面的两个定位机构实现板材在传输过程中的定位;通过沿焊缝方向布置与传输方向成β夹角的压紧轮保证板材传输位置精度;采用焊缝碾压精密预成型机构降低非线性定位误差带来的间隙,保证了长焊缝激光拼焊的质量。新型激光拼焊定位、夹紧机构能完成任意长度和异形料片的定位与夹紧。非线性定位误差是制约长焊缝激光拼焊的瓶颈,焊缝碾压精密预成型是解决非线性定位误差的主要手段,为了指导焊缝碾压机构的设计,对焊缝碾压精密预成型原理与实现技术展开了深入研究:建立了碾压预成型数学模型;研究了碾压过程中金属塑性流动规律;研究了基于Kriging模型的机构优化方法建立全局优化模型,实现了碾压轮机构优化设计;提出了基于曲柄滑块原理的碾压轮机构,碾压轮和薄板压紧轮同轴并采用两端支撑,提高了碾压机构刚度并实现薄板压紧轮与碾压轮竖直方向相对位置的调节,以适应不同板厚差板材焊缝的碾压预成型。以上述理论为指导,建立了碾压预成型试验平台,碾压试验结果表明:碾压预成型机构能够有效解决超长焊缝非线性定位误差问题,能够消除最大为0.3mm的焊缝间隙。本文研究了激光拼焊定位、夹紧机构误差对焊接质量的影响及其误差补偿方法。通过工艺试验研究,建立了机构误差对焊缝界面形状影响的数学模型,完善了激光焊接工艺对机构误差的补偿机制,研究了碾压在激光拼焊中的特点及作用。

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The ionospheric parameter M(3000)F2 (the so-called transmission factor or the propagation factor) is important not only in practical applications such as frequency planning for radio-communication but also in ionospheric modeling. This parameter is strongly anti-correlated with the ionospheric F2-layer peak height hmF2,a parameter often used as a key anchor point in some widely used empirical models of the ionospheric electron density profile (e.g., in IRI and NeQuick models). Since hmF2 is not easy to obtain from measurements and M(3000)F2 can be routinely scaled from ionograms recorded by ionosonde/digisonde stations distributed globally and its data has been accumulated for a long history, usually the value of hmF2 is calculated from M(3000)F2 using the empirical formula connecting them. In practice, CCIR M(3000)F2 model is widely used to obtain M(3000)F2 value. However, recently some authors found that the CCIR M(3000)F2 model has remarkable discrepancies with the measured M(3000)F2, especially in low-latitude and equatorial regions. For this reason, the International Reference Ionosphere (IRI) research community proposes to improve or update the currently used CCIR M(3000)F2 model. Any efforts toward the improvement and updating of the current M(3000)F2 model or newly development of a global hmF2 model are encouraged. In this dissertation, an effort is made to construct the empirical models of M(3000)F2 and hmF2 based on the empirical orthogonal function (EOF) analysis combined with regression analysis method. The main results are as follows: 1. A single station model is constructed using monthly median hourly values of M(3000)F2 data observed at Wuhan Ionospheric Observatory during the years of 1957–1991 and compared with the IRI model. The result shows that EOF method is possible to use only a few orders of EOF components to represent most of the variance of the original data set. It is a powerful method for ionospheric modeling. 2. Using the values of M(3000)F2 observed by ionosondes distributed globally, data at grids uniformly distributed globally were obtained by using the Kriging interpolation method. Then the gridded data were decomposed into EOF components using two different coordinates: (1) geographical longitude and latitude; (2) modified dip (Modip) and local time. Based on the EOF decompositions of the gridded data under these two coordinates systems, two types of the global M(3000)F2 model are constructed. Statistical analysis showed that the two types of the constructed M(3000)F2 model have better agreement with the observational M(3000)F2 than the M(3000)F2 model currently used by IRI. The constructed models can represent the global variations of M(3000)F2 better. 3. The hmF2 data used to construct the hmF2 model were converted from the observed M(3000)F2 based on the empirical formula connecting them. We also constructed two types of the global hmF2 model using the similar method of modeling M(3000)F2. Statistical analysis showed that the prediction of our models is more accurate than the model of IRI. This demonstrated that using EOF analysis method to construct global model of hmF2 directly is feasible. The results in this thesis indicate that the modeling technique based on EOF expansion combined with regression analysis is very promising when used to construct the global models of M(3000)F2 and hmF2. It is worthwhile to investigate further and has the potential to be used to the global modeling of other ionospheric parameters.

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Stochastic reservoir modeling is a technique used in reservoir describing. Through this technique, multiple data sources with different scales can be integrated into the reservoir model and its uncertainty can be conveyed to researchers and supervisors. Stochastic reservoir modeling, for its digital models, its changeable scales, its honoring known information and data and its conveying uncertainty in models, provides a mathematical framework or platform for researchers to integrate multiple data sources and information with different scales into their prediction models. As a fresher method, stochastic reservoir modeling is on the upswing. Based on related works, this paper, starting with Markov property in reservoir, illustrates how to constitute spatial models for catalogued variables and continuum variables by use of Markov random fields. In order to explore reservoir properties, researchers should study the properties of rocks embedded in reservoirs. Apart from methods used in laboratories, geophysical means and subsequent interpretations may be the main sources for information and data used in petroleum exploration and exploitation. How to build a model for flow simulations based on incomplete information is to predict the spatial distributions of different reservoir variables. Considering data source, digital extent and methods, reservoir modeling can be catalogued into four sorts: reservoir sedimentology based method, reservoir seismic prediction, kriging and stochastic reservoir modeling. The application of Markov chain models in the analogue of sedimentary strata is introduced in the third of the paper. The concept of Markov chain model, N-step transition probability matrix, stationary distribution, the estimation of transition probability matrix, the testing of Markov property, 2 means for organizing sections-method based on equal intervals and based on rock facies, embedded Markov matrix, semi-Markov chain model, hidden Markov chain model, etc, are presented in this part. Based on 1-D Markov chain model, conditional 1-D Markov chain model is discussed in the fourth part. By extending 1-D Markov chain model to 2-D, 3-D situations, conditional 2-D, 3-D Markov chain models are presented. This part also discusses the estimation of vertical transition probability, lateral transition probability and the initialization of the top boundary. Corresponding digital models are used to specify, or testify related discussions. The fifth part, based on the fourth part and the application of MRF in image analysis, discusses MRF based method to simulate the spatial distribution of catalogued reservoir variables. In the part, the probability of a special catalogued variable mass, the definition of energy function for catalogued variable mass as a Markov random field, Strauss model, estimation of components in energy function are presented. Corresponding digital models are used to specify, or testify, related discussions. As for the simulation of the spatial distribution of continuum reservoir variables, the sixth part mainly explores 2 methods. The first is pure GMRF based method. Related contents include GMRF model and its neighborhood, parameters estimation, and MCMC iteration method. A digital example illustrates the corresponding method. The second is two-stage models method. Based on the results of catalogued variables distribution simulation, this method, taking GMRF as the prior distribution for continuum variables, taking the relationship between catalogued variables such as rock facies, continuum variables such as porosity, permeability, fluid saturation, can bring a series of stochastic images for the spatial distribution of continuum variables. Integrating multiple data sources into the reservoir model is one of the merits of stochastic reservoir modeling. After discussing how to model spatial distributions of catalogued reservoir variables, continuum reservoir variables, the paper explores how to combine conceptual depositional models, well logs, cores, seismic attributes production history.

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均匀布点采集百花湖表层水样44个, 对水样不同形态汞含量进行了分析, 并现场测定水质参数采用经典统计学与半变异函数拟合相结合的方法, 研究了百花湖表层水中不同形态汞含量的空间变异性根据半变异函数拟合的结果, 在ArcGIS软件的支持下进行克立格插值, 以此来揭示百花湖表层水中不同形态汞含量的空间分布规律研究表明百花湖表层水中的汞污染主要来自上游, 随水体流动汞污染减少但也有一些区域可能因富营养化而使颗粒态汞和总汞含量增加

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We report findings from a choice experiment survey designed to estimate the economic benefits of policy measures to improve the rural landscape in the Republic of Ireland. Using a panel mixed logit specification to account for unobserved taste heterogeneity we derived individual-specific willingness-to-pay (WTP) estimates for each respondent in the sample. We subsequently investigated the spatial dependence of these estimates. Results suggest the existence of positive spatial autocorrelation for all rural landscape attributes. As a means of benefit transfer, kriging methods were employed to interpolate WTP estimates across the whole of the Republic of Ireland. The kriged WTP surfaces confirm the existence of spatial dependence and illustrate the implied spatial variation and regional disparities in WTP for all the rural landscape improvements investigated.

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A problem with use of the geostatistical Kriging error for optimal sampling design is that the design does not adapt locally to the character of spatial variation. This is because a stationary variogram or covariance function is a parameter of the geostatistical model. The objective of this paper was to investigate the utility of non-stationary geostatistics for optimal sampling design. First, a contour data set of Wiltshire was split into 25 equal sub-regions and a local variogram was predicted for each. These variograms were fitted with models and the coefficients used in Kriging to select optimal sample spacings for each sub-region. Large differences existed between the designs for the whole region (based on the global variogram) and for the sub-regions (based on the local variograms). Second, a segmentation approach was used to divide a digital terrain model into separate segments. Segment-based variograms were predicted and fitted with models. Optimal sample spacings were then determined for the whole region and for the sub-regions. It was demonstrated that the global design was inadequate, grossly over-sampling some segments while under-sampling others.

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The ability to predict the behavior of masonry materials is crucial to conserve building stone. Natural stone, such as sandstone, is not immune from the processes of weathering in the built environment and suffers from decay by granular disintegration, contour scaling, and multiple flaking. Spatial variation of rock properties is a major contributing factor to inconsistent responses to weathering. This has implications for moisture movement and salt input and output and storage, and results in unpredictability in the decay dynamics of masonry materials. This article explores the use of variography and kriging to investigate the spatial interactions between the trigger factors of stone decay, in particular, permeability and its effect on salt penetration. Sandstone blocks were used to represent fresh building stones from a weathering perspective and gave baseline characteristics for the interpretation of subsequent deterioration and decay pathways. Simulated weathering trials involved preloading a sandstone block with salt and subjecting a separate block to 20 cycles of a weathering trial designed to simulate a temperate weathering regime. Geostatistical analysis indicated differences in the spatial variation of permeability of the fresh rock and that subjected to the weathering regimes. Spatial prediction and visualization showed differences in the spatial continuity of permeability in a horizontal and vertical direction through the preloaded block after salt weathering. Continual wetting with salt and alternate heating increased permeability in a vertical direction, enabling the ingress and movement of salt and moisture more effectively through the stone.

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This paper explores how the surface permeability of sandstone blocks changes over time in response to repeated salt weathering cycles. Surface permeability controls the amount of moisture and dissolved salt that can penetrate in and facilitate decay. Connected pores permit the movement of moisture (and hence soluble salts) into the stone interior, and where areas are more or less permeable soluble salts may migrate along preferred pathways at differential rates. Previous research has shown that salts can accumulate in the near-surface zone and lead to partial pore blocking which influences subsequent moisture ingress and causes rapid salt accumulation in the near-surface zone.

Two parallel salt weathering simulations were carried out on blocks of Peakmoor Sandstone of different volumes. Blocks were removed from simulations after 2, 5, 10, 20 and 60 cycles. Permeability measurements were taken for these blocks at a resolution of 20 mm, providing a grid of 100 permeability values for each surface. The geostatistical technique of ordinary kriging was applied to the data to produce a smoothed interpolation of permeability for these surfaces, and hence improve understanding of the evolution of permeability over time in response to repeated salt weathering cycles.

Results illustrate the different responses of the sandstone blocks of different volumes to repeated salt weathering cycles. In both cases, after an initial subtle decline in the permeability (reflecting pore blocking), the permeability starts to increase — reflected in a rise in mean, maximum and minimum values. However, between 10 and 20 cycles, there is a jump in the mean and range permeability of the group A block surfaces coinciding with the onset of meaningful debris release. After 60 cycles, the range of permeability in the group A block surface had increased markedly, suggesting the development of a secondary permeability. The concept of dynamic instability and divergent behaviour is applied at the scale of a single block surface, with initial small-scale differences across a surface having larger scale consequences as weathering progresses.

After cycle 10, group B blocks show a much smaller increase in mean permeability, and the range stays relatively steady — this may be explained by the capillary conditions set up by the smaller volume of the stone, allowing salts to migrate to the ‘back’ of the blocks and effectively relieving stress at the ‘front’ face.