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.     

Calculation of the added mass of circular cylinders in shallow water

The added mass of hull section shapes must be known, in order to carry out any studies of ship motions, which may be associated with either seakeeping or manoeuvring. Determination of the added mass in deep water can involve conformal mapping or surface singularity distributions. However, in shallow water the problem of determining the added mass is made more difficult by the proximity of the seabed. In this paper, three approaches to the problem of finding the added mass of semi-circular sections are explored. Although there is no known exact solution to this problem, the relationships given by the three methods are compared and the approximate nature of the solutions is examined. The first method is a series solution, which is taken here to include more terms than are normally given in the existing literature. The other two solutions are considered to be new, and so are given in some mathematical detail.     

空间信息网格中远程空间连接查询的优化

随着空间信息网格的建设,网格平台上管理的空间信息资源越来越丰富,这促进了空间信息网格中空间数据分布式查询的应用需求,而在分布式空间查询中,空间连接查询操作往往成为性能的瓶颈.根据空间信息的特点,通过利用网格计算资源来优化空间连接查询的执行.首先基于网格服务构建网格平台分布式空间数据查询软件结构,通过设计远程空间连接执行服务利用网格平台中的计算资源;根据空间信息的特点.采用基于Kd-Tree空间分区并行连接的方法提高远程空间数据连接操作执行效率,并给出了远程空间连接执行的查询代价模型;然后根据连接代价模型设计了远程空间连接查询执行计划优化生成算法;最后总结了本文工作并探讨了下一步研究方向.     

关于角平分线法建立线状缓冲区算法的改进

分析了用对角平分线法建立缓冲区的算法,提出了一种新的求角平分线和缓冲点的方法,实践证明其在算法实现方面是可行的,而且效果比较理想。     

内蒙古大青山地区寒武系与奥陶系之间的一个重要的层序界面

大青山地区寒武纪－奥陶纪地层分布零星，是由中生代逆冲推覆构造就位于此的一系列近东西向延展的构造岩片组成。下寒武统色麻沟组直接覆盖在太古界变质岩之上，缺失中元古界什那干群，寒武系与奥陶系之间呈假整合接触，标志着区内寒武纪与奥陶纪之间发生过一次抬升构造运动，其形成机制与古亚洲洋内的稳定陆快向华北板块拼贴事件有关，是早奥陶世末期华北板块整体抬升的序幕。这个层序界面的认识，对于恢复华北板块北部边缘构造演化历史具有重要意义。     

山东惠民凹陷中央隆起带古近系沙河街组层序地层特征及控制因素研究

结合山东惠民凹陷中央隆起带古近系层序地层学研究,依据层序中湖平面变化特点和相应的沉积物特征,提出了构造运动和气候是本区层序地层发育的主要控制因素。中央隆起带古近系沙河街组二、三、四亚段可划分为 3种层序类型,即断陷初期型、强断陷期型和断陷后期型层序。由于构造运动导致湖岸线向盆地方向退缩,产生下降体系域,本次研究采用了体系域的四分法,即一个完整层序由低位、湖侵、高位和下降四个体系域组成,并且层序界面位于湖平面最大下降的位置,介于下降域和低位域之间。断陷初期红色地层层序,受气候因素控制明显,既不同于冲积地层层序,也不同于正常湖相地层层序,在层序演化上有其独特的特点。受构造作用和沉积物补给条件的影响,研究区发育三种沉积密集段,不同类型的沉积密集段在层序中所处位置不同,控制着不同的烃源岩厚度和油气资源储量。     

Ion acoustic instability of HPT particles,FAC density,anomalous resistivity and parallel electric field in the auroral region

During the magnetic storm of 21st March 1990, the DE-1 spacecraft encountered the auroral region at high invariant latitude at altitudes ranging from a few thousand kilometers in the ionosphere to many earth radii in the magnetosphere. The magnetic field perturbations interpretable as field aligned current (FAC) layers and the electrostatic turbulence possibly due to electrostatic ion acoustic instability driven by these currents are shown. The critical drift velocity of Hot Plasma Torus (HPT) electrons and the growth rate of ion acoustic wave as a function of electron to ion temperature ratio (T _e/T_i) for low and high current densities and energy of HPT electrons are found out. The intense FAC destabilizes the ion acoustic wave and the resultant electrostatic turbulence creates an anomalous resistivity. The current driven resistivity produces parallel electric field and high power dissipation. The anomalous resistivityη, potential difference along the auroral field lines V_t|, intensity of electric field turbulenceE _t| and power produced per unit volumeP are computed. It is found that the change in westward magnetic perturbation increasesJ _t|, η, V_t|, E_t| andP. Hence HPT electrons are heated and accelerated due to power dissipation during magnetically active periods in the auroral region. Concerning, applications, such HPT electrons can be used in particle accelerators like electron ring accelerator, smokatron etc.     

螺旋坐标下的因子分解合成炮叠前深度偏移

在合成炮叠前深度偏移的基础上，提出了一种高效的合成炮叠前深度偏移方法，即在螺旋坐标下用因子分解进行波场外推的混合法. 用因子分解进行波场外推分为因果过程和反因果过程两个显式求解过程. 这种螺旋坐标下的显式求解过程,提高了波场外推的效率. 根据相位编码原理,对多个射线参数的合成波场进行了编码叠加,基于射线参数实现了MPI并行计算,进一步提高了计算效率. 在推导了有关公式并进行定量分析之后,对Marmousi复杂模型进行了计算,并作了比较,结果表明本文方法具有精度高和速度快的特点,可用于实际资料的计算.     

松辽盆地白垩系的密集段及海水进侵的新证

在总结松辽盆地白恶系层地层特征的基础上，阐述了密集段的地质学和地球物理学标志，经分析，大多数重要反射与密集段相关而并非是层序边界，根据扫描电镜分析结果，在密集段中首次发现了钙质超微化石，为区内白垩纪海水进侵的提供了新的证据，由稳定同位素分析，密集段形成了缺氧，相对可容纳空间最大及水体最深时期。