A machine learning approach for predicting computational intensity and domain decomposition in parallel geoprocessing

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.     

ECOLOGICAL SERIES OF SOIL ANIMALS IN DARLIDAI MOUNTAIN

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.     

小波分析理论在GPS技术中的应用

在GPS数据处理中 ,存在着误差影响、影响波的干扰、周跳和数据量大等问题。误差影响和影响波的干扰实质是在接收卫星信号时受到其它因素的影响 ;周跳是由于卫星信号的失锁而造成信号的不连续 ;数据量大是因为GPS观测需要采样间隔小又连续观测所致。由于小波理论具有时频分析、波形分解、特征提取和快速小波变换等特性 ,应用小波变换和波形分解可以解决误差影响和影响波的干扰的问题 ;应用特征提取可以解决周跳检测问题 ;应用快速小波变换可进行数据压缩     

ANALYSIS OF DRIVING FORCES ON THE CHANGE OF HISTORICAL FARMLAND USE IN SHANDONG PROVINCE DURING THE QING DYNASTY (1644-1911)

1INTRODUCTIONTheIGBP-IHDP(InternationalGeosphere-BiosphereProgramme,andInternationalHumanDimensionPro-gramme)jointproject—LUCC(landuse/coverchange)isaninterdisciplinaryprogramdesignedtoimprovetheunderstandingofthedynamicsofland-useandland-coverchangeasinputstoandconsequencesofglobalenvironmentalchangeandsustainabledevelopment(CHARLOTTE,2002).Inparticularthedifferentbio-geochemicalmodeling(e.g.theglobalcarboncycle)ac-tivitiesandcomparativestudies,suchasthoseconduct-edbyIGBP-G…     

蜕壳素对凡纳滨对虾生长及表观消化率的影响

研究了外源性蜕皮激素对凡纳滨对虾生长和表观消化率的影响 ,实验时在基础饲料中分别添加 0 .1%、0 .2 %、0 .4 %的两种市售蜕壳素产品 ,制成 6种外源性脱壳素配合饲料 ,不添加的基础饲料作为对照组 ,试验在 2 6 0L玻璃钢循环水养殖系统中 ,每个剂量组设 3个重复 ,8周生长试验结果表明 :市售蜕壳素产品能有效地促进对虾生长 ,试验结束时 ,试验组虾体增重分别较对照组增加 16 .8%、7.5 2 %、5 .9%、11.4 %、2 9.0 7%、16 .5 3% ,但是凡纳滨对虾对饲料粗蛋白的表观消化率没有明显地提高 ,凡纳滨对虾对脂肪的表观消化率较低。推算凡纳滨对虾饲料中最佳蜕皮酮添加量为 6 0mg/kg。     

差分法周跳探测与修复方法改进

在目前常用的周跳探测与修复方法基础上 ,提出了首先将观测资料按照观测历元不连续分成若干小弧段 ,然后利用差分法进行周跳探测 ,根据差分后周跳放大的特性判断周跳和野值 ,并确定其位置利用宽带组合和电离层组合的方法解算周跳大小。通过实例验证了其有效性。     

富氏谱分析法模拟地壳垂直运动的地学依据及其策应力模型

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     

Optical Flash of GRB 990123: Constraints on the Physical Parameters of the Reverse Shock

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.     

维生素E醋酸酯对鱼油脂肪酸含量变化的影响

新鲜鱼油中添加05、0、2505、00 mg/kg 4种不同浓度的维生素E醋酸酯,在实验的第6、14、28、36和68天测定鱼油中的脂肪酸含量。结果表明:在500 mg/kg添加量内,维生素E醋酸酯对鱼油中脂肪酸含量没有显著性影响(P>0.05)。在实验期间,EPA(C20:5)、DHA(C22:6)、亚油酸(C18:2)含量明显下降,ARA(C20:4)、亚麻酸(C18:3)先升后降,棕榈酸(C16:1)逐步上升;C14含量逐渐增加,C17则先降后升,C16和C18在实验后期有较大提高。维生素E醋酸酯对鱼油中不饱和脂肪酸效用系数大小依次为:ARA>EPA>DHA>C18:3>0>C16:1>C18:2>C18:1,对ARA抗氧化效用最大,效用系数达到10.193%,C20:5为0.490%,C22:6为0.364%;维生素E醋酸酯对饱和脂肪酸效用系数大小依次为:C14>C17>0>C18>C16。     

Silicon limitation on primary production and its destiny in Jiaozhou Bay, China——Ⅳ：Study on cross-bay transect from estuary to ocean

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.