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.     

An approximate method for evaluating the shear band thickness in saturated soils

A formula for the thickness of a shear band formed in saturated soils under a simple shear or a combined stress state has been proposed. It is shown that the shear band thickness is dependent on the pore pressure properties of the material and the dilatancy rate, but is independent of the details of the combined stress state. This is in accordance with some separate experimental observations. Copyright © 2004 John Wiley & Sons, Ltd.     

地倾斜台站数字化、模拟观测数据频率特性研究

分析了四川、云南的部分地倾斜数字化观测与模拟观测资料的特性，从频率范围，周期10天以上的FFT谱特性，固体潮波振幅，相位特征值等方面，论述了地倾斜数字化资料较模拟记录资料的信息组成变化，并对资料的分析与应用进行了初步探讨。     

Neutrino mass,luminosity variation,and spectrum of SN1987A

In this paper, the neutrino mass has been determined from SN1987a observation in a manner that the simultaneity of neutrino emission is not regarded as the starting point, but is itself defined through the analysis by Monte-Carlo simulation. The result is that the neutrino mass lies in 3–4 eV, possiblym _v 3.6 eV. Neutrino luminosity variation and neutrino spectrum are also obtained. Comparison with theories gives further support to the mass determination, and also predicts the mass of progenitor star of SN1987a to be in the range of 12–25M .The project supported by the National Natural Science Foundation of China.     

Possible chemical structures and biological precursors of different vitrinites in coal measure in Northwest China

Chemical structure of Jurassic vitrinites isolated from the coals in basins in NW China have been checked using solid state ¹³C NMR and flash pyrolysis-GC/MS. Study shows some Jurassic collodetrinites are rich in aliphatic products in pyrolysates, consisting with the high amount of methylene carbon in ¹³C NMR spectra. In contrast, pyrolysates of Jurassic collotelinites are rich in phenols and alkylbenzenes. Also one Pennsylvanian and one Permian vitrinite selected from the Ordos basin, NW China have been checked for comparison. The proportion of aliphatics is low in pyrolysates, and aliphatic carbon peak in ¹³C NMR spectrum of Permian vitrinite is mostly composed of gas-prone carbons compared with collodetrinites in those Jurassic basins. But both pyrolysis and ¹³C NMR data shows the Pennsylvanian vitrinite is not only gas-prone but also oil-prone. Relatively high proportion of long chain aliphatic structure of some Jurassic vitrinite in Junggar, Turpan-Hami basins may be due to the contribution of liptodetrinites, which may be included during the formation of vitrinites. And it seems that suberinite is the most possible precursor of long chain aliphatics in the structure of Jurassic collodetrinite.     

Identification of sources and causes of leakage on a zoned earth dam in northern Taiwan: Hydrological and isotopic evidence

Seepage through an earth dam body must be regulated as a well–planned process, if it is not properly managed, the abnormal seepage may cause dam failure. This study employed stable isotopic and statistical methods to identify the source and cause of an abnormal leakage on the zoned earth dam of the Xin–Shan reservoir located in northern Taiwan. Water samples from the dam area over a 2-a period were collected and analyzed for their stable O and H isotope compositions. In addition, a 4-a period of hydrological data, including rainfall, reservoir level, well level, seepage of filter drainage and leakage, were statistically analyzed with a stepwise multiple regression approach. Both the stable isotopic and hydrological results indicate that the abnormal leakage on the dam shell comes from the filter drainage in the dam. The reason for abnormal leakage is due to unexpected and significant precipitation–sourced water flowing into the dam’s body. The dam filter fails to drain out the incoming water sufficiently, thus generating the abnormal seepage. In addition, the defect in the dam filter may also cause the drainage filter to drain off reservoir seepage inadequately. Therefore, it is suggested that checking the filter function and preventing excessive precipitation–sourced water from flowing into the dam are the two top priorities for the follow-up remedial strategy of the dam.     

黄、渤海沿岸海冰测点代表性浅析

通过分析１９８０年以后的海冰资料和卫星云图照片，对黄、渤海沿岸１１个海冰测点的历史变迁进行了评述，浅析了测点的优劣及使用资料时应注意的事项。     

大鹏澳海域水体磷的形态及其分布特征

根据１９９２年１２月（冬季）和１９９３年７月（夏季）对大鹏澳海域２４ｈ定点连续观测和夏季大面调查，统计了该海域各种形态磷的变化范围和平均含量；计算了各种形态磷分别占总磷（ＴＰ）和总溶解磷（ＴＤＰ）的百分比；讨论了各种形态磷之间的相互关系；分析了影响ＴＰ和ＴＤＰ分布的环境因素。     

碘－钒盐催化下合成的四溴邻苯二甲酸酐

报道一种新的有效催化剂－碘－钒盐和在一定条件下合成四溴邻苯二甲酸酐的方法。探讨催化剂的组成配比、用量、温度及废酸循环使用等因素对合成方法的影响。该催化剂的催化效果和常用的碘、碘－铁催化剂相同，适用于四溴邻苯二甲酸酐的合成。     

海桑属红树植物遗传多样性和引种关系研究

以海南东寨港红树林自然保护区内无瓣海桑(Sonneratia apetala)、海南海桑(S.hainanensis)、拟海桑(S.paracaseolaris)、杯萼海桑(S.abla)、大叶海桑(S.ovata)、海桑(S.caseolaris)等6种海桑属红树植物为材料,对15个有效引物进行RAPD分析,共扩增出512条带,其中多态性条带为297,占总扩增条带的58.01%.Nei指数法分析和UPGMA统计分析表明,6种海桑属红树植物分为A,B,C3个组,平均遗传距离为0.38.A组包括无瓣海桑、海南海桑、大叶海桑、怀萼海桑,其中无瓣海桑、海南海桑、大叶海桑处于同一个亚组.B组包括拟海桑.C组包括海桑.对海南和福建无瓣海桑种群进行RAPD分析.对Shannon表型多样性指数统计结果表明,福建种群为0.669,海南种群为0.671,各种群遗传变异较大,这与无瓣海桑种群广泛的适应性相一致.对种群间的Shannon表型多样性指数分析表明,种群内的遗传变异占整个遗传变异的93.3%,而种群间的遗传变异仅占6.7%.这表明无瓣海桑种群的大部分遗传变异存在于种群内,而种群间的遗传变异较小.由此可见,无瓣海桑基因组丰富的多样性,是使其由海南成功引种到福建的重要因素.