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1.
ABSTRACT

High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning.  相似文献   
2.
This paper presents an introductory overview of recently developed stochastic theories for tackling spatial variability problems in predicting groundwater flow and solute transport. Advantages and limitations of the theories are discussed. Lastly, strategies based on the stochastic approaches to predict solute transport in aquifers are recommended.  相似文献   
3.
The structure, functioning and hydrodynamic properties of aquifers can be determined from an analysis of the spatial variability of baseflow in the streams with which they are associated. Such analyses are based on simple low‐cost measurements. Through interpreting the hydrological profiles (Q = f(A)) it is possible to locate the aquifer(s) linked to the stream network and to determine the type of interrelated flow, i.e. whether the stream drains or feeds the aquifer. Using an analytical solution developed for situations with a positive linear relationship, i.e. where the baseflow increases linearly with increasing catchment size, it is also possible to estimate the permeability of the aquifer(s) concerned at catchment scale. Applied to the hard‐rock aquifers of the Oman ophiolite, this method shows that the ‘gabbro’ aquifer is more permeable than the ‘peridotite’ aquifer. As a consequence the streams drain the peridotites and ‘leak’ into the gabbro. The hydrological profiles within the peridotite are linear and positive, and indicate homogeneity in the hydrodynamic properties of these formations at the kilometre scale. The permeability of the peridotite is estimated at 5 · 10?7 to 5 · 10?8 m/s. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   
4.
对边界层理论新结果中出现的一类奇异积分方程w(t)=∫1 t(1-s)(λ+λs+s)/w(s)ds+(1-t)∫t 0s/w(s)ds,t∈(0,1)进行讨论,并得出了上述方程在λ∈(-1/2,0)上正解存在性的新结果。  相似文献   
5.
Analysis of Zn, Cu, Pb, Co, Cr, Li, Ni, K, Al, Fe extracted by 1 mol/L HCl or 0.5 mol/LHCl/H_2O_2, showed concentrations of Zn, Cu, Pb, Co, Cr, Fe, Ni were significantly correlated with Li, Al,K, and clay. Two methods are used to indicate the background value of the non-residual phase of elementsin sediments, and are the same as the methods used to indicate the background value of totalconcentrations in sediments. The first method uses correlograms and regression equations,the second usesthe mean element concentrations normalized with grain size. Li, Al, K can be used as reference elements to determine the background value of Zn, Cu, Pb, Co,Cr, Ni, Fe, while the clay concentration's correlation with some extractable concentrations can be used tocalculate the background value of the non-residual phase of elements as a percentage of clay concentrationin the sediments. Based on this study, the concept of using the background value of the non-residualphase of elements to compare the pollution level in differ  相似文献   
6.
One zone modeling of the irregular variability of red super-giants is intended with regard to the nonlinear coupling of finite amplitude pulsation with convection. The nonlocal mixing length is employed for the evaluation of the convective flux, the turbulent pressure and the turbulent power of temperature fluctuations. The radial pulsation and the Boussinesq convection are assumed for simplicity. The one zone is defined as the layer having the entropy maximum and the minimum at the bottom and at the top, respectively. The quasi-adiabatic approximation is consistent with this definition in fixing the zone to the same mass range. The spatial derivatives are evaluated under the assumption of homologous changes with the equilibrium homologous parameters. Then, a set of 6 simultaneous first order nonlinear ordinary differential equations are obtained as the one zone representation of the irregular variability of the convective envelope.  相似文献   
7.
对L1 范估计的平差值和LS估计的平差值作为抗差估计的初值进行了比较 ,指出在 ρ函数是严凸函数时 ,二者无明显的区别。因为LS估计简单且易于计算 ,因此建议用LS估计的平差值作为抗差估计的初值。  相似文献   
8.
1995年7月11日—12日,广西地矿厅和河池地区行署首次联合举办矿产资源勘查成果展销会,会址设在河池市,与会代表130余人。展销会提交大会展销的矿产资源勘查成果38项,引资勘查项目38项。经买卖双方三天的洽谈,涉及到的项目25项,会议期间签订矿产资源勘查成果合同协议4项,愈千万元,取得较好的社会经济效益。为地勘资金多渠道来源开辟了新路子,对促进地勘单位地质找矿工作及勘查成果有偿使用发挥了重要作用  相似文献   
9.
笔者曾对广西芒场锡多金属矿田的稳定同位素进行研究。本文根据硫、铅、氢、氧、碳等稳定同位素组成和锶的初始值提供的信息.探讨了矿床成因。并结合矿田矿床地质特征、控矿条件及有关统计参数,参考前人对矿床认识的基础上,修正提出了该矿田混合热液成矿模式,可供类似矿床研究和找矿的参考。  相似文献   
10.
用遗传算法解算病态方程   总被引:7,自引:1,他引:6  
对应用遗传算法解决病态方程问题进行了探讨。利用拟合法而不是通过法方程求解参数,从而避免了法方程系数求逆,使病态方程的解答有了较好的结果。通过模拟计算并和其他方法进行比较,证明该方法是可行的和有效的。  相似文献   
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