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.     

Mobile Agent系统结构及其关键技术

Mobile Agent技术是一门新兴的技术,具有移动性、智能性和异步计算的特点,已成为计算机网络和分布式系统最具活力的发展方向.现对Mobile Agent的概念、系统结构及其关键技术进行了分析和探讨.     

The Relation between the Amplitude and the Period of Solar Cycles

The maximum amplitudes of solar activity cycles are found to be well anti-correlated (r = -0.72) with the newly defined solar cycle lengths three cycles before (at lag -3) in 13-month running mean sunspot numbers during the past 190 years. This result could be used for predicting the maximum sunspot numbers. The amplitudes of Cycles 24 and 25 are estimated to be 149.5±27.6 and 144.3±27.6, respectively.     

DISASTER ANALYSIS AND COUNTERMEASURES OF LAND SUBSIDENCE CAUSED BY COAL CUTTING IN CHINA

In recent years, many coal-producing countries have paid great attention to the land subsidence causedby coal cutting. In China, because of the dense population in coalfield areas, the land subsidence hazard is more seri-ous. After a brief analysis on the mechanism of land subsidence, this paper gives a comprehensive and systematical ac-count on all kinds of hazards caused by the land subsidence in China. The study shows that land subsidence has endan-gered land, buildings, traffic and communication lines, dykes and dams. It also causes damage to ecological and socialenvironment. In order to lessen the hazard of land subsidence, preventive measures should be taken to reduce the col-lapse amount, such as extraction with stowing, banded mining system, succession and coordination mining system, orhigh-pressure mudflow between rock strata. Measures of reinforcing or moving certain buildings should also be taken toreduce the destructive degree. In order to harness the subsidence land and bring them under control for fanning, mea-sures should be taken such as filling with spoil or fine breeze, excavating the deeper and covering the shallower land.     

南水北调东线水质污染和湖泊水生经济的系统分析

本文讨论了我国南水北调东线水质污染的产生及其对调水水质的影响,同时对调水区域内工业排水与治理经济模式和湖泊水生经济系统的最优化分析进行了探论.     

形变大地测量学的进展、问题与地震预报

简要概括了形变大地测量学的革命性进展，研讨了它的科学特色、功能和定义以及对地球科学和防灾减灾的推动。形变大地测量学有助于从根本上击破多年来制约地震预报的“瓶颈”，但也存在不少急待解决的问题。着重研讨了在21世纪前10年，形变大地测量学如何依托多年的学科积累并充分受益于人造卫星和数字化等新技术，开展创新性研究和试验以推进地震预报。为此，对当前的研究工作提出了12条科学技术途径。最后对学科名称提出了建议。     

长江三峡工程地壳形变监测网络

长江三峡工程地壳形变监测网络，采用了当今高精度GPS、INSAR空间大地测量技术，并与精密水准测量，精密重力测量，精密激光测距和峒体连续形变监测等技术相结合，构成一个空间上点、线、面结合，时间上长、中、短兼顾的高精度，高时空分辨率的地壳形变监测网络。该网络既可获取三峡库区特别是库首区区域形变场和区域应变场的动态变化，监测库区主要断层活动，为水库诱发地震预测及研究服务，又可用于气象、滑坡地质灾害监测等，该监测网络于1997年底开始建设，2001年6月建成，到目前为止，已获得大量宝贵的观测资料，必将产生显著的经济效益和社会效益。     

新疆塔中南坡奥陶系的地层缺失和沉积相变化

按照奥陶系内部6个组沉积的时间片段拟定塔中南坡不同区块存在不同程度的缺失。部分关键层段的牙形石和几丁虫组合特征证明一间房组和恰尔巴克组在塔中部分井区是存在的,但恰尔巴克组的分布范围最狭窄。总体上,塔中南坡隆起区地层缺失较多,古城墟隆起基本完整。据缺失状况和岩相展布,显示塔中南坡的沉积单元具有由东往西迁移的特征,且各时段迁移的距离与速度存在较大差异。     

Distribution of Cd,Pb, Zn and Cu and their chemical speciations in soils from a peri-smelter area in northeast China

An exploratory study on soil contamination of heavy metals was carried out surrounding Huludao zinc smelter in Liaoning province, China. The distribution of total heavy metals and their chemical speciations were investigated. The correlations between heavy metal speciations and soil pH values in corresponding sites were also analyzed. In general, Cd, Zn, Pb, Cu and As presented a significant contamination in the area near the smelter, comparied with Environmental Quality Standards for Soils in China. The geoaccumulation index showed the degree of contamination: Cd > Zn > Pb > Cu > As. There was no obvious pollution of Cr and Ni in the studied area. The speciation analysis showed that the dominant fraction of Cd and Zn was the acid soluble fraction, and the second was the residual fraction. Pb was mostly associated with the residual fraction, which constituted more than 50% of total concentration in all samples. Cu in residual fraction accounted for a high percentage (40–80%) of total concentration, and the proportion of Cu in the oxidizable fraction is higher than that of other metals. The distribution pattern of Pb and Zn was obviously affected by soil pH. It seemed that Pb and Zn content in acid solution fraction increased with increasing soil pH values, while Cd content in acid soluble fraction accounted for more proportion in neutral and alkaline groups than acidic one. The fraction distribution patterns of Cu in three pH groups were very similar and independent of soil pH values. And the residual fraction of Cu took a predominant part (50%) of the total content.