虚拟天文台数据访问系统(VO-DAS)任务调度设计与实现     

田海俊  刘超  高丹  路勇  杨阳  崔辰州  赵永恒  郑小平 《天文研究与技术》2011,8(1)

为解决异地、异构、海量天文数据无缝透明地统一访问,中国虚拟天文台(China-VO)研究小组自主设计并开发了一套解决方案——虚拟天文台数据访问系统(VO-DAS)。着重从执行流程、设计模式、Session机制、生命周期、资源销毁、异常处理等模块详细阐述了该系统的任务调度设计。为了验证该系统的可行性和性能,最后描述了多个天文科学范例。  相似文献   

虚拟地理环境研究进展与理论框架   总被引：3，自引：0，他引：3  

龚建华  周洁萍  张利辉 《地球科学进展》2010,25(9):915-926

阐述虚拟地理环境的形成、发展与研究现状,并从"虚拟现实技术"与"虚拟现实"的相互关系探讨虚拟地理环境基本概念.从基本思想、系统结构、在线参与者社会组织水平、与GIS/数字地球的关系等角度,分析虚拟地理环境的特征.从数据、模型、表现以及协同4个方面,讨论了虚拟地理环境系统建设的关键技术与研究前沿.尝试建立了一个虚拟地理环境基本理论初步研究框架,认为在地理哲学思想层次应该重点研究复杂性人地系统、地理虚/实关系论、地理/遥感信息本体论,在地理/地理信息科学层次需要重点研究地理认知与思维、地理相似原理、地理计算模拟;同时讨论虚拟地理环境与面向"人"的地理信息科学、基于虚拟地理环境地理科学方法论,以及可计算人地关系的相关理论问题.  相似文献   

支持向量回归机在滑坡安全可靠度评价中的应用研究   总被引：1，自引：0，他引：1  

杨栋  姜黎 《地下水》2010,32(1):141-142,145

探讨支持向量机的参数优化方法,将学习能力较强的支持向量机引入滑坡可靠度评价当中,并根据数理统计的理论,对滑坡稳定性敏感性因素作数据处理,并证明其合理性,在此基础上提出一种改进的可靠度指标的计算方法。为便于对比,分别选取49个学习样本和121个学习样本两种计算模型,计算实例表明,这两种计算模型与蒙特卡洛模型计算结果非常接近,充分体现了在小样本的情形下支持向量机的优势,说明将其应用于滑坡安全可靠度评价中是可行的。  相似文献   

Novel Folded-PCA for improved feature extraction and data reduction with hyperspectral imaging and SAR in remote sensing     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

As a widely used approach for feature extraction and data reduction, Principal Components Analysis (PCA) suffers from high computational cost, large memory requirement and low efficacy in dealing with large dimensional datasets such as Hyperspectral Imaging (HSI). Consequently, a novel Folded-PCA is proposed, where the spectral vector is folded into a matrix to allow the covariance matrix to be determined more efficiently. With this matrix-based representation, both global and local structures are extracted to provide additional information for data classification. Moreover, both the computational cost and the memory requirement have been significantly reduced. Using Support Vector Machine (SVM) for classification on two well-known HSI datasets and one Synthetic Aperture Radar (SAR) dataset in remote sensing, quantitative results are generated for objective evaluations. Comprehensive results have indicated that the proposed Folded-PCA approach not only outperforms the conventional PCA but also the baseline approach where the whole feature sets are used.  相似文献   

Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping     

《ISPRS Journal of Photogrammetry and Remote Sensing》2014

Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas.  相似文献   

通过软硬变化检测识别冬小麦   总被引：1，自引：0，他引：1  

朱爽  张锦水  帅冠元  喻秋艳 《遥感学报》2014,18(2):476-496

提出一种软硬变化检测的作物识别方法 SHLUCD(Soft and Hard Land Use/Cover Change Detection Method)。该方法利用多期遥感影像能够有效表达作物的生长物候特征,以达到在离散变化区(即纯净像元区,包括完全转换成作物的突变区域和非作物区域)和连续变化区(即渐变区,混合像元区,是部分转化为作物的区域)准确进行作物的识别。在北京市选择一个研究区,以冬小麦为研究对象,选用2011年10月6日(播种期)和2012年4月16日(拔节期)两期环境减灾1号卫星影像,分别采用硬变化检测方法 HLUCD(Hard Land Use/Cover Change Detection Method)、软变化检测方法 SLUCD(Soft Land Use/Cover Change Detection Method)和SHLUCD进行冬小麦的识别。实验结果表明:在不同尺度窗口下,SHLUCD较传统方法表现出较明显的优势,具有更低的均方根误差RMSE(SHLUCD为[0.14,0.07],HLUCD为[0.15,0.07],SLUCD为[0.16,0.08])和偏差bias(SHLUCD为-0.0008,HLUCD为-0.007,SLUCD为0.014)和更高的决定系数R2(SHLUCD为[0.68,0.86],HLUCD为[0.62,0.86],SLUCD为[0.60,0.86])。针对冬小麦突变区域、冬小麦渐变区域和非冬小麦区域分别进行评价,表明SHLUCD识别精度接近各区最佳的识别方法,进一步验证了SHLUCD的灵活性和适用性。SHLUCD方法在离散变化区能够通过土地覆盖类型状态变化来有效地识别出冬小麦,在连续变化区可识别出土地覆盖的状态变化程度定量表达冬小麦的丰度,是其他作物多时相遥感变化检测的前期实验基础。  相似文献   

The educational space of global online higher education     

《Geoforum》2014

This article explores how standards and codes for collaboration in international higher education influence the educational space of global online education and the way it functions within the context of international development aid. Firstly the article discusses the educational space of higher education and the geography of education whereby the aim is to situate global online education within the on-going discourse on standards in higher education, international development aid, and the knowledge economy. The article then examines a qualitative case study of an Internet-based masters programme attended by students from Europe and Africa. A main focus of the empirical analysis is the students’ experience of being geographically immobile while collaborating online internationally, including how this circumstance affected their motivation and participation and the benefits of the programme. In the concluding discussion it is argued that even though online collaboration among students and educational institutions is not entirely equal, common standards created a space in which positions were challenged and practices were changed over the course of online participation.  相似文献   

Virtual Field Geologic Trip System     

Jian Wang  Linfu Xue  Xiaojun Zhou 《世界地质(英文版)》2003,6(2)

Virtual Field Geologic Trip System (VFGTS) constructed by the technique of visualization can efficiently present geologic field information and widely used in the field of geologic education. This paper introduces the developing thinking of VFGTS and discusses the main implement processes. Building VFGTS mainly includes systemically gathering of field geological data, the building of virtual geological world, and displaying of virtual geologic world and human-computer interaction.  相似文献   

基于模式识别理论的卡钻类型判别分析          下载免费PDF全文

吴军  臧艳彬  陈星星 《探矿工程》2015,42(10):31-34

将模式识别理论中的支持向量机、Bayes判别分析以及多元回归分析应用于卡钻类型判别分析,建立了基于模式识别理论的卡钻判别模型。以近几年川东北卡钻数据为例进行了算例分析,结果表明：采用支持向量机、Bayes判别法及多元回归法对卡钻类型判别的结果与实际结果的误判率分别为1.92%,11.52%,61.54%。支持向量机（SVM）判别结果精度最高,但其判别方程式较为复杂,不能直观看出各分量对结果的影响程度;多元回归分析判别方程形式简单,可以直观表达各参量与卡钻之间的密切程度,但其判别精度较低;Bayes判别法计算精度介于二者之间,但其判别精度与判别式的个数密切相关。  相似文献   

样本输入方式对极端学习机预报日长变化的影响     

雷雨  蔡宏兵  赵丹宁 《天文研究与技术》2015,(3)

针对极端学习机(Extreme Learning Machine,ELM)用于日长(Length-Of-Day,LOD)变化预报过程中,样本输入方式对预报结果的影响进行了研究。采用跨度、连续和迭代3种样本输入方式对日长变化进行预报。结果表明,不同的样本输入方式对预报结果有很大影响,样本按跨度输入的预报精度最低;样本采用连续输入方式在短期和中长期预报中预报精度较高,但计算速度较慢,较适合中长期预报;样本按迭代输入方式的短期预报精度稍优于连续输入方式,而中长期预报精度则不如连续输入方式,但具有较高的预报效率。这对于日长变化的实时快速预报有着较高的现实意义。  相似文献