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

Peng Yue  Fan Gao  Boyi Shangguan  Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274

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   

The monopole moment of the three-point correlation function of the two-degree Field Galaxy Redshift Survey     

Jun Pan  István Szapudi 《Monthly notices of the Royal Astronomical Society》2005,362(4):1363-1370

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

X. B. Lu  Wang Shuyun  Wang Yihua  Peng Cui 《国际地质力学数值与分析法杂志》2004,28(15):1533-1541

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.  相似文献   

GPS/LEO掩星观测的变分同化技术   总被引：6，自引：0，他引：6  

刘敏  郭鹏 《天文学进展》2006,24(1):27-42

在简单介绍GPS/LEO掩星探测大气的发展历史和科学意义之后,详细阐述了反演的基本原理;分析了标准反演中存在的问题,并说明一维变分同化(1DVAR)在反演方法中的重要性;给出了一维变分同化中价值函数的求解,以及各种同化因子;简单介绍了对当前气象学中普遍使用的四维变分同化(4DVAR);重点讨论了各种同化方法,以及使用各种同化因子的优缺点。最后,通过CHAMP卫星的观测实例分析,验证了GPS数据在数值天气预报(NWP)中的作用,以及相对于标准反演法一维变分对气象要素的改进。  相似文献   

Approach to Mountain Hazards in Tibet, China   总被引：1，自引：1，他引：0  

MADongtao TUJianjun CUIPeng LURuren 《山地科学学报》2004,1(2):143-154

Tibet is located at the southwest boundary of China. It is the main body of the Qinghai-Tibet Plateau, the highest and the youngest plateau in the world. Owing to complicated geology, Neo-tectonic movements, geomorphology, climate and plateau environment, various mountain hazards, such as debris flow, flash flood, landslide, collapse, snow avalanche and snow drifts, are widely distributed along the Jinsha River (the upper reaches of the Yangtze River), the Nu River and the Lancang River in the east, and the Yarlungzangbo River, the Pumqu River and the Poiqu River in the south and southeast of Tibet. The distribution area of mountain hazards in Tibet is about 589,000 km^2, 49.3% of its total territory. In comparison to other mountain regions in China, mountain hazards in Tibet break out unexpectedly with tremendously large scale and endanger the traffic lines, cities and towns, farmland, grassland, mountain environment, and make more dangers to the neighboring countries, such as Nepal, India, Myanmar and Bhutan. To mitigate mountain hazards, some suggestions are proposed in this paper, such as strengthening scientific research, enhancing joint studies, hazards mitigation planning, hazards warning and forecasting, controlling the most disastrous hazards and forbidding unreasonable human exploring activities in mountain areas.  相似文献   

一次西南低涡过程的地面场中尺度分析     

曾俊  卢敬华  潘鄂芬 《成都信息工程学院学报》1990,(Z1)

本文运用带通滤波分析方法,对四川省1981年7月由西南低涡等天气系统引起的大暴雨过程作了地面气象要素场的中尺度诊断分析。结果表明,带通滤波后的场具有明显的中尺度特征,其中一些物理量场的适当配置与6小时后的暴雨中心有较好的对应关系。说明了此带通滤波方法在实际业务预报中具有一定的使用价值。  相似文献   

北部湾北部海上油田发现历程     

钟铿  潘其云 《南方国土资源》1997,(2)

北部湾北部海上油田的开发工作始于５０年代，６０～７０年代作了大量地质工作。改革开放后，油气勘查取得突破性进展。累计发现油气构造６个，含油面积超过４０ｋｍ２，石油地质储量约４亿ｔ，已开发油田２个，揭开我国南方油气资源开发序幕  相似文献   

Optical monitoring of the quasar 4C 38.41     

B. Peng  J. Wu  X. Zhou 《Monthly notices of the Royal Astronomical Society》2003,346(2):483-488

The results of a photometric monitoring of the quasar 4C 38.41, performed at the optical R and B bands in 2002 February–March, are presented. With a 60/90 cm Schmidt telescope at the Xinglong station of the National Astronomical Observatories of China, we observed the source exhibiting amplitude variations of up to 0.78 mag in both bands during the whole campaign. Intraday and even intranight variations are detected as well. A typical variability time-scale of about 36 d is derived from our 2-month observations at the optical bands, which is identical to that found at a radio wavelength of 92 cm, suggesting a common origin for the variations in 4C 38.41 from optical to radio bands.  相似文献   

SIMULATION AND PREDICTION OF DEBRIS FLOW USING ARTIFICIAL NEURAL NETWORK     

WANGXie-kang HUANGEr CUIPeng 《中国地理科学(英文版)》2003,13(3):262-266

Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed.  相似文献   

γ射线暴的研究进展（Ⅳ：特强γ射线暴和软γ重复暴   总被引：2，自引：0，他引：2  

陆建隆  潘善龙  陆埮 《天文学进展》1996,14(4):302-314

最近CGRO上的仪器观测到了两个迄今为止发现的最强的λ暴GB930131和GB940217,其光子最高能量均达GeV量级;GB930131的峰值计数率达2×10~6个光子s~(-1);而GB940217的持续时间竟长达90min。另外沉寂了多年的软重复暴源SGR1900 14和SGR1806-20的再次爆发也由BATSE发现。一系列的观测还发现这些软重复暴均与X射线源对应且与超新星遗迹成协。文中对特强暴和软重暴(SGR)的性质及研究进展作了较为详细的评述。  相似文献