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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.
ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN   总被引:1,自引:0,他引:1  
The ecological series of soil animals under the broad-leaved and pine mixed forest in Darlidai Mountainwas studied. Seven sample plots were selected according to different altitude gradients, which belong to different vegeta-tion types. By investigating and analyzing soil animals in every sample plot it is found that there are 45 groups and 1956individuals, which axe involved in 3 phylums, 7 classes, 16 orders, respectively. The altitude is a key factor which af-fects ecological series of soil animals. Both the groups and individuals of soil animals increase with altitude increasingunder certain conditions, which contrastes with ordinary cases, resulting from special micro-climate in studied area. Thegroups and individuls of soil animals are the most under the broad-leaved and pine forest on the top of the mountain, andthe least under Picea-Abies forest in the foot of the mountain.  相似文献   
3.
应用GPS观测青藏高原东北缘应力场变化   总被引:2,自引:0,他引:2  
采用各向同性弹性地球模型推导了地面位移场速率与地壳内任意点应力场变化的边界积分关系,同时利用青藏高原东北缘1999~2001年观测的GPS资料对观测区地壳深度为5 km和25 km的主应力和最大剪应力进行了计算分析.结果表明,青藏高原东北缘的主应力变化主要集中在祁连山断裂、海原断裂等,在1920~1954年间历史上发生过多次震级为7.0~8.5级强震的断裂附近,并具有主应力变化沿断层走向分布、最大剪应力沿断层走向交替变化等特征.  相似文献   
4.
应用地壳波浪与镶嵌构造学说对富氏谱分析法提取地壳垂直形变信息的科学性做了地质学意义上的阐释 ,并提出了根据多期形变资料提取特定波段上构造策应力的数学模型  相似文献   
5.
The optical flash accompanying GRB 990123 is believed to be powered by the reverse shock of a thin shell. With the best-fit physical parameters for GRB 990123 and the assumption that the parameters in the optical flash are the same as in the afterglow, we show that: 1) the shell is thick rather than thin, and we have provided the light curve for the thick shell case which coincides with the observation; 2) the theoretical peak flux of the optical flash accounts for only 3×10~-4 of the observed. In order to remove this discrepancy, the physical parameters, the electron energy and magnetic ratios, εe and εB, should be 0.61 and 0.39, which are very different from their values for the late afterglow.  相似文献   
6.
The authors analyzed the data collected in the Ecological Station Jiaozhou Bay from May 1991 to November 1994, including 12 seasonal investigations, to determine the characteristics, dynamic cycles and variation trends of the silicate in the bay. The results indicated that the rivers around Jiaozhou Bay provided abundant supply of silicate to the bay. The silicate concentration there depended on river flow variation. The horizontal variation of silicate concentration on the transect showed that the silicate concentration decreased with distance from shorelines. The vertical variation of it showed that silicate sank and deposited on the sea bottom by phytoplankton uptake and death, and zooplankton excretion. In this way, silicon would endlessly be transferred from terrestrial sources to the sea bottom. The silicon took up by phytoplankton and by other biogeochemical processes led to insufficient silicon supply for phytoplankton growth. In this paper, a 2D dynamic model of river flow versus silicate concentration was established by which silicate concentrations of 0.028–0.062 μmol/L in seawater was yielded by inputting certain seasonal unit river flows (m3/s), or in other words, the silicate supply rate; and when the unit river flow was set to zero, meaning no river input, the silicate concentrations were between 0.05–0.69 μmol/L in the bay. In terms of the silicate supply rate, Jiaozhou Bay was divided into three parts. The division shows a given river flow could generate several different silicon levels in corresponding regions, so as to the silicon-limitation levels to the phytoplankton in these regions. Another dynamic model of river flow versus primary production was set up by which the phytoplankton primary production of 5.21–15.55 (mgC/m2·d)/(m3/s) were obtained in our case at unit river flow values via silicate concentration or primary production conversion rate. Similarly, the values of primary production of 121.98–195.33 (mgC/m2·d) were achieved at zero unit river flow condition. A primary production conversion rate reflects the sensitivity to silicon depletion so as to different phytoplankton primary production and silicon requirements by different phytoplankton assemblages in different marine areas. In addition, the authors differentiated two equations (Eqs. 1 and 2) in the models to obtain the river flow variation that determines the silicate concentration variation, and in turn, the variation of primary production. These results proved further that nutrient silicon is a limiting factor for phytoplankton growth. This study was funded by NSFC (No. 40036010), and the Director's Fund of the Beihai Sea Monitoring Center, the State Oceanic Administration.  相似文献   
7.
提要 本文详细讨论了一种三维重力位场快速正反演方法。作者在前人工作的基础上,对算法作了行之有效的改进,通过对反演中的不稳定因素进行各种理论模型试算,得出保证迭代反演稳定收敛的准则,编制出可在微型机IBM—PC上运行的人机对话式自动正反演程序。本文还对各种不均质模型进行了模似计算并将该方法应用于某含油气沉积盆地的双层界面构造研究,揭示出了储油有利地段。  相似文献   
8.
It has become clear in recent years that relativistic beaming is a good explanation for the BL Lac phenomenon. Of studies based on the relativistic beaming model of BL Lac objects, we note that the orientation of jet's axis to the line-of-sight is very small and, therefore, the observed flux emitted from a rapidly moving source is orders of magnitude higher than the flux in its rest-frame:F obs = 3 + F intr, where is the bulk relativistic Doppler factor. Then the observed apparent magnitudem v must be corrected for this effect. For our 39 samples, the corrected apparent magnitudem v corr and logZ have a good correlation.  相似文献   
9.
遗迹化石在层序地层学研究中的应用   总被引:2,自引:0,他引:2  
以济阳坳陷古近系沙河街组和塔里木盆地志留系为例,探讨了遗迹化石与层序地层学的关系,表现在3个方面:1)层序界面的识别层序界面位置发育有特征性的受基底控制的遗迹相,且界面上下遗迹组合类型发生变化;2)准层序界面的识别较深水环境中,界面上下生物扰动强度明显差异,界面之下扰动强度较大,扰动指数可达到3,而界面之上几乎没有生物扰动,且在同一准层序内部,由下至上,扰动强度逐渐增大;3)旋回层序的识别:在潮控滨线环境中,单个准层序内部,由下至上,高能环境的Skolithos遗迹组合逐渐变为中低能环境的Planolites-Palaeophycus遗迹组合和低能环境的Cochlichnus-Planolites遗迹组合,由下至上呈现旋回性变化特征。  相似文献   
10.
西藏东巧蛇绿岩中辉长岩锆石SHRIMP定年及其地质意义   总被引:9,自引:0,他引:9  
东巧蛇绿岩位于分割羌塘地块和拉萨地块的班公湖—怒江缝合带中段,是该带最著名的产铬铁矿床的蛇绿岩残片之一。该蛇绿岩遭受构造肢解,恢复后的蛇绿岩剖面各岩石单元齐全。本文应用SHRIMPⅡ锆石UPb法,对东巧蛇绿岩中堆晶辉长岩进行了测年,获得辉长岩年龄为187.8±3.7 Ma。该年龄代表了东巧洋盆的形成时代,为确定研究区特提斯洋盆的古构造格局及其发育演化过程等提供了重要的年代学制约。  相似文献   
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