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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.
A micropolar elastoplastic model for soils is formulated and a series of finite element analyses are employed to demonstrate the use of a micropolar continuum in overcoming the numerical difficulties encountered in application of finite element method in standard Cauchy–Boltzmann continuum. Three examples of failure analysis involving a deep excavation, shallow foundation, and a retaining wall are presented. In all these cases, it is observed that the length scale introduced in the polar continuum regularizes the incremental boundary value problem and allows the numerical simulation to be continued until a clear collapse mechanism is achieved. The issue of grain size effect is also discussed. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   
3.
A closed‐form deflection response of a beam rest is presented in this paper using the integral transform method. The theory of linear partial differential equations is used to represent the deflection of beam subjected to a moving harmonic line load in integration form. The solution is finally carried out using the inverse Fourier transform. To evaluate the integration analytically, poles of the integrand are identified with the help of algebraic equation theory. Residue theorem is then utilized to represent the integration as a contour integral in the complex plane. Closed‐form deflections and numerical results are provided for different combinations of load frequency and velocity. Copyright © 2002 John Wiley & Sons, Ltd.  相似文献   
4.
成生于冰碛扇内,经一定的生物、物理、化学成矿作用,以砂金形态分布而富集成矿的金矿称为冰碛扇型砂金矿床。它具有沿造山带一定标高范围成群、成带分布,沉积物为近源且半胶结,砂金呈面状分布,并以粒金、块金为主,具胶状、浑圆状、包块状构造形态,分布极不均匀等特征。冰碛扇型砂金矿床的成矿作用与河成砂金矿床有本质的区别。它的成矿作用模式是:造山带下地壳富含的活化金通过新构造运动活化的断裂运移地表,经地下流体和地表流体的迁移聚集到冰碛扇这一封闭稳定的生物、物理、化学障环境中,主要经高效聚金微生物有机胶体成矿作用沉淀、再生加大形成砂金,逐步富集成矿床。而红色磨拉石建造中风化离解的Fe,Mn物质对沉淀环境pH值起着一定的调节作用。冰碛扇型砂金矿床在我国西部造山带内广泛分布,具有一定的工业价值,是砂金矿床中一重要类型,应予以重视  相似文献   
5.
1 HYDROLOGIC FEATURES Lingdingyang Estuary, located at the middle south of Guangdong Province, is a bell-shaped estuary with a north-south direction. Its area is about 2100km2. The north of Qi′ao Island and Inner-Lingding Island, and the south of Humen are grouped as Neilingdingyang Estuary, having an area of 1041km2. Affected by topography, runoff and tide, its dynamic condition is very complicated. Different water areas have different hydrologic features. The topography under …  相似文献   
6.
基于统一强度理论的地基临界荷载公式   总被引:1,自引:0,他引:1  
基于统一强度理论,按照临界荷载公式的推导方法,得到地基临界荷载的统一解公式。Mohr-Coulomb强度理论计算的结果为其特例。把计算结果与《建筑地基基础设计规范》中的结果进行了对比分析,认为当不同程度地考虑中间主应力σ2的影响时,可以有效地发挥地基的强度潜能。并通过实例计算了统一强度理论参数b取不同值时地基承载力特征值,并进行了对比分析。  相似文献   
7.
提出一种基于负反馈权值的动态网络负载调度算法。算法主要用在多出口路由器上,其执行效率高,开销小。基于算法的多出口路由器不仅能够很好的保持出口间的负载均衡。还具有良好的出口容错性能。  相似文献   
8.
Sediments contained in the river bed do not necessarily contribute to morphological change. The finest part of the sediment mixture often fills the pores between the larger grains and can be removed without causing a drop in bed level. The discrimination between pore‐filling load and bed‐structure load, therefore, is of practical importance for morphological predictions. In this study, a new method is proposed to estimate the cut‐off grain size that forms the boundary between pore‐filling load and bed‐structure load. The method evaluates the pore structure of the river bed geometrically. Only detailed grain‐size distributions of the river bed are required as input to the method. A preliminary validation shows that the calculated porosity and cut‐off size values agree well with experimental data. Application of the new cut‐off size method to the river Rhine demonstrates that the estimated cut‐off size decreases in a downstream direction from about 2 to 0·05 mm, covariant with the downstream fining of bed sediments. Grain size fractions that are pore‐filling load in the upstream part of the river thus gradually become bed‐structure load in the downstream part. The estimated (mass) percentage of pore‐filling load in the river bed ranges from 0% in areas with a unimodal river bed, to about 22% in reaches with a bimodal sand‐gravel bed. The estimated bed porosity varies between 0·15 and 0·35, which is considerably less than the often‐used standard value of 0·40. The predicted cut‐off size between pore‐filling load and bed‐structure load (Dc,p) is fundamentally different from the cut‐off size between wash‐load and bed‐material load (Dc,w), irrespective of the method used to determine Dc,p or Dc,w. Dc,w values are in the order of 10?1 mm and mainly dependent on the flow characteristics, whereas Dc,p values are generally much larger (about 100 mm in gravel‐bed rivers) and dependent on the bed composition. Knowledge of Dc,w is important for the prediction of the total sediment transport in a river (including suspended fines that do not interact with the bed), whereas knowledge of Dc,p helps to improve morphological predictions, especially if spatial variations in Dc,p are taken into account. An alternative to using a spatially variable value of Dc,p in morphological models is to use a spatially variable bed porosity, which can also be predicted with the new method. In addition to the morphological benefits, the new method also has sedimentological applications. The possibility to determine quickly whether a sediment mixture is clast‐supported or matrix‐supported may help to better understand downstream fining trends, sediment entrainment thresholds and variations in hydraulic conductivity.  相似文献   
9.
在野外考察过程中,于新疆乌恰地区早侏罗世康苏组沼泽相砂岩层中,发现并识别出软沉积物液化变形层,变形包括负载构造,球枕构造及卷曲变形构造。通过模拟试验的对比研究认为,该软沉积物变形机制与液化作用有关,触发沉积物液化的动力是古地震,并且根据地震震级与液化最大震中距的关系,推测出造成早侏罗世软沉积物变形的里氏地震震级为6相似文献   
10.
新疆境内塔拉斯-费尔干纳断裂早侏罗世走滑的古地震证据   总被引:11,自引:2,他引:9  
在野外考察过程中,于新疆乌恰地区早侏罗世康苏组沼泽相砂岩层中,发现并识别出软沉积物液化变形层,变形包括负载构造,球-枕构造及卷曲变形构造。通过模拟试验的对比研究认为,该软沉积物变形机制与液化作用有关,触发沉积物液化的动力是古地震,并且根据地震震级与液化最大震中距的关系,推测出造成早侏罗世软沉积物变形的里氏地震震级为6相似文献   
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