基于社交媒体数据挖掘的旅游者情绪感知

随着智能移动终端和社交媒体的普及,带有地理标签的社交媒体数据大量涌现,其“文本—位置—时间”的多维特征使得精细时空尺度上的旅游者情绪感知成为可能。该文基于2017-2019年旅游者发布的新浪微博数据,采用BERT模型对微博数据进行文本分析,探讨旅游者情绪的时空分布规律及不同主题下旅游者的情绪特征,并分析导致旅游者产生负面情绪的相关因素。研究发现,微博中旅游者情绪呈现昼夜、周和季节性节律变化,不同性别旅游者在情绪反应强度及情绪节律上存在差异,对“天气”和“餐饮”主题易产生强烈情绪。该文提出的旅游者情绪挖掘方法可从多维度、多层次挖掘旅游者情绪特征,为旅游目的地舆情监测和预警系统提供借鉴。     

地震叠前时间偏移的一种图形处理器提速实现方法

新近发展的图形处理器（GPU,Graphic Processing Unit）通用计算技术,现已日趋实用成型,并获得诸多应用领域的广泛关注.对油气勘探专项资料处理技术的运用而言,概因GPU与中央处理器（CPU）的计算性能的甚大差异,致使GPU这一通用计算技术在石油工业中的应用研究正在有效开展.本文仅借助于油气勘探中广泛使用的叠前时间偏移,旨在于扼要阐明其基于GPU应用的有效性;文中还提出一种利用GPU实现地震叠前时间偏移的软件构件方法,并针对非对称走时叠前时间偏移所拓展的应用软件提供一种具体实现架构.与以往用个人计算机（PC,Personal Computer）或者PC集群所用的叠前时间偏移相比,本文方法可甚大地提高计算效率,从而在石油物探资料处理中可显著地节约计算成本和维护费用.文中实际例证也表明,基于GPU进行高性能并行计算,当是适应目前石油工业中大规模计算需求的一个重要发展途径.     

A parallel evolutionary strategy based simulation–optimization approach for solving groundwater source identification problems

Groundwater characterization involves the resolution of unknown system characteristics from observation data, and is often classified as an inverse problem. Inverse problems are difficult to solve due to natural ill-posedness and computational intractability. Here we adopt the use of a simulation–optimization approach that couples a numerical pollutant-transport simulation model with evolutionary search algorithms for solution of the inverse problem. In this approach, the numerical transport model is solved iteratively during the evolutionary search. This process can be computationally intensive since several hundreds to thousands of forward model evaluations are typically required for solution. Given the potential computational intractability of such a simulation–optimization approach, parallel computation is employed to ease and enable the solution of such problems. In this paper, several variations of a groundwater source identification problem is examined in terms of solution quality and computational performance. The computational experiments were performed on the TeraGrid cluster available at the National Center for Supercomputing Applications. The results demonstrate the performance of the parallel simulation–optimization approach in terms of solution quality and computational performance.     

Spectral element analysis on the characteristics of seismic wave propagation triggered by Wenchuan <Emphasis Type="Italic">M</Emphasis><Subscript>s</Subscript>8.0 earthquake

The 2008 Wenchuan earthquake occurred in an active earthquake zone, i.e., Longmenshan tectonic zone. Seismic waves triggered by this earthquake can be used to explore the characteristics of the fault rupture process and the hierarchical structure of the Earth’s interior. We employ spectral element method incorporated with large-scale parallel computing technology, to investigate the characteristics of seismic wave propagation excited by Wenchuan earthquake. We calculate synthetic seismograms with one-point source model and three-point source model respectively. The AK135 model is employed as a prototype of our numerical global Earth model. The Earth’s ellipticity, Earth’s medium attenuation, and topography data are taken into consideration. These wave propagation processes are simulated by solving three-dimensional elastic wave governing equations. Three-dimensional visualization of our numerical results displays the profile of the seismic wave propagation. The three-point source, which is proposed from the latest investigations through field observation and reverse estimation, can better demonstrate the spatial and temporal characteristics of the source rupture process than the one-point source. We take comparison of synthetic seismograms with observational data recorded at 16 observatory stations. Primary results show that the synthetic seismograms calculated from three-point source agree well with the observations. This can further reveal that the source rupture process of Wenchuan earthquake is a multi-rupture process, which is composed by at least three or more stages of rupture processes. Supported by National Basic Research Program of China (Grant No. 2004CB418406), National Natural Science Foundation of China (Grant Nos. 40774049 and 40474038), and Computer Network Information Center, Chinese Academy of Sciences (Grant No. INF105-SCE-02-12)     

基于三维非线性有限元的边坡稳定分析方法

刚体极限平衡法不能反映岩体中实际的应力分布,而基于有限元的强度折减系数法在判断收敛性方面存在一些问题。为了解决这些问题,采用多重网格法,分别建立用于有限元计算的结构网格和用于计算滑面稳定安全系数的滑面网格,可以方便地获得任意滑面或滑块的稳定安全系数,从而将非线性有限元和极限平衡分析结合起来。为了提高计算规模和计算精度,采用有限元并行计算程序TFINE.Pfem进行计算,分析了网格密度对计算结果精度的影响,并应用于锦屏高边坡的稳定分析中。与刚体极限平衡法结果的对比分析表明,由于考虑了计算过程中的非线性应力调整,该方法的计算结果比刚体极限平衡法偏大,而且更符合实际情况。     

基于粗细网格的有限元并行分析方法

并行计算己成为求解大规模岩土工程问题的一种强大趋势。探讨了粗细网格与预处理共轭梯度法结合的并行有限元算法。从多重网格刚度矩阵推得有效的预处理子。该算法在工作站机群上实现。用地基处理时土体强夯的数值模拟分析进行了数值测试,对其并行性能进行了详细分析。计算结果表明：该算法具有良好的并行加速比和效率,是一种有效的并行算法。     

相邻结构的高效阻尼控制

提出了相邻结构高效阻尼控制的概念,并基于双液缸的放大原理提出了一处相应的装置,该装置通过放大相邻结构间的振动差别,使阻尼器具有更大的变形和速度,从而更高效地工作,文章阐明了该装置的工作原理,建立了两相邻结构高效阻尼控制体系的运动方程,并对此进行了计算机仿真分析,结果表明,高效阻尼控制的概念是正常的,本文提出的控制装置是有效的,可取得远优于普通阻尼控制的效果。     

Simplified seismic sidesway collapse analysis of frame buildings

This paper presents the development and assessment of a simplified procedure for estimating the seismic sidesway collapse margin ratio of building structures. The proposed procedure is based on the development of a robust database of seismic peak displacement responses of nonlinear single‐degree‐of‐freedom systems for various seismic intensities and uses nonlinear static (pushover) analysis without the need for nonlinear time history dynamic analysis. The proposed simplified procedure is assessed by comparing its collapse capacity predictions on 72 different building structures with those obtained by nonlinear incremental dynamic analyses. The proposed simplified procedure offers a simple, yet efficient, computational/analytical tool that is capable of predicting collapse capacities with acceptable accuracy for a wide variety of frame building structures. Copyright © 2013 John Wiley & Sons, Ltd.     

面向大规模空间Agent建模的分布式地理模拟框架

基于Agent建模的地理模拟是认识和理解动态地理现象的有效方法,但随着地理模拟的规模和复杂性不断增加,模型的计算问题开始凸显。分布式并行仿真是解决大规模Agent复杂模拟计算的途径,然而已有研究基于Agent建模/仿真软件构建并行仿真系统的方式并不适用于具有高移动与行为交互的空间Agent建模及其模拟过程的实时可视化。为解决这个问题, 本文提出了一个分布式地理模拟框架DGSimF,用于大规模动态空间Agent模拟,支持模拟过程的实时表示与分析。设计了一个简单但高效的时空数据模型建模空间Agent,支持直接基于Agent行为建模集成地学模型,采用了时间微分方法协同各计算节点行为的执行,实现以“任务并行”的方式进行分布式计算以提高仿真性能,构建了基于三维地球渲染引擎的虚拟地理环境,提供模拟过程的实时可视化。最后,以“红蓝对抗”案例进行了实验验证,对不同模拟计算量和不同客户端数量下的仿真性能进行了分析,结果表明DGSimF可以为具有时空特征变化与行为交互的大规模空间Agent模拟提供一个有效的平台。通过扩展计算节点,DGSimF可以有效地缓解复杂模拟计算的压力问题,并且仿真性能较高,在实验中并行效率保持在0.7以上。     

Python在短临气象预报检验中的应用

基于机器学习方法的短临多气象要素预报系统(Weather Elements Nowcasting based on machine learning,简称WEN)具有高发布频次、高时间分辨率、基于候和时辰的复杂预报模型等特点。应用多维标签数组、机器学习工具、并行计算框架等Python库,以快速计算为目标,建立以预报模型覆盖时间范围为统计检验时间边界的检验子系统,客观给出预报性能,为模型调优效果评估、产品业务化运行提供依据。