基于步进电机的位移促动器设计与实测     

张宗猛  王正兰  杨德华  吴常铖  金振宇 《天文研究与技术》2019,(3):329-334

以环形太阳望远镜为应用背景,研制了一种基于步进电机的位移促动器,并进行了性能测试实验,获得了位移促动器的性能指标。分析了常见的大行程、高精度位移促动器的结构形式,选择位移缩放式作为位移促动器的基本结构。该位移促动器采用步进电机集成行星减速器作为驱动元件,以具有特殊消间隙结构的螺旋传动作为位移缩放机构,为实现高分辨率、高刚度和高精度的位移促动器设计,开展了位移促动器的性能测试实验,结果表明:该位移促动器轴向位移量程为±2 mm,不同负载下均能实现1 μm的步长分辨率,位移闭环输出精度优于1 μm。研制的位移促动器为环形太阳望远镜的建设提供重要的技术支持,并为其它精密光学镜面支撑系统的工程应用提供参考。  相似文献   

经验模态分解和最小二乘支持向量机在大坝变形预测中的应用     

刘嘉 《北京测绘》2019,33(1):101-105

由于受到温度、雨水冲刷等外在因素的影响,大坝变形时间序列数据会呈现出非线性和非平稳的曲线特性。为此,提出一种经验模态分解(EMD)和最小二乘支持向量机(LSSVM)相结合的大坝变形预测模型。首先,使用EMD对大坝变形时间序列数据分解成若干个不同尺度的本征模式分量(IMF);然后,利用LSSVM模型对各个IMF进行预测;最后,对预测的结果相加得到大坝变形预测值。以吉林市丰满大坝为算例,构建EMD-LSSVM预测模型,并与LSSVM模型对比分析,结果表明,EMD-LSSVM模型预测效果更好,精度更高,具有更好的实用型。  相似文献   

Vegetation species mapping in a coastal-dune ecosystem using high resolution satellite imagery     

Anabella Medina Machín  Javier Marcello  Antonio I. Hernández-Cordero  Javier Martín Abasolo  Francisco Eugenio 《地理信息系统科学与遥感》2019,56(2):210-232

Vegetation mapping is a priority when managing natural protected areas. In this context, very high resolution satellite remote sensing data can be fundamental in providing accurate vegetation cartography at species level. In this work, a complete processing methodology has been developed and validated in a complex vulnerable coastal-dune ecosystem. Specifically, the analysis has been carried out using WorldView-2 imagery, which offers spatial and spectral resolutions. A thorough assessment of 5 atmospheric correction models has been performed using real reflectance measures from a field radiometry campaign. To select the classification methodology, different strategies have been evaluated, including additional spectral (23 vegetation indices) and spatial (4 texture parameters) information to the multispectral bands. Likewise, the application of linear unmixing techniques has been tested and abundance maps of each plant species have been generated using the library of spectral signatures recorded during the campaign. After the analysis conducted, a new methodology has been proposed based on the use of the 6S atmospheric model and the Support Vector Machine classification algorithm applied to a combination of different spectral and spatial input data. Specifically, an overall accuracy of 88,03% was achieved combining the corrected multispectral bands plus a vegetation index (MSAVI2) and texture information (variance of the first principal component). Furthermore, the methodology has been validated by photointerpretation and 3 plant species achieve significant accuracy: Tamarix canariensis (94,9%), Juncus acutus (85,7%) and Launaea arborescens (62,4%). Finally, the classified procedure comparing maps for different seasons has also shown robustness to changes in the phenological state of the vegetation.  相似文献   

基于SVM的海浪要素预测试验研究          下载免费PDF全文

金权  华锋  杨永增 《海洋科学进展》2019,37(2):199-209

采用支持向量机对海浪要素中的有效波高进行预测,采用风场和波浪场作为学习要素,对比不同特征向量对有效波高预测结果的准确度。取台湾岛东部海区作为实验区域,使用NCEP再分析的数值模式数据作为学习样本。选用支持向量分类机,建立了4组不同特征向量的模型进行海浪有效波高的预测,并对4种模型的结果进行比较和分析。实验表明,当输入的特征向量过多或过少时,会对模型的预测结果和计算效率产生不同的影响。当使用风场和波浪场共同作为特征向量进行学习时,在该区域预测结果与模式预报结果相比更接近,相关系数将近99%,均方根误差约0.2 m。  相似文献   

Assessing Worldview-3 multispectral imaging abilities to map the tree diversity in semi-arid parklands     

《International Journal of Applied Earth Observation and Geoinformation》2020

Semi-arid parkland agrosystems are strongly sensitive to climate change and anthropic pressure. In the context of sustainability research, trees are considered critical for various ecosystem services covering environment quality as well as food security and health. But their actual ecological impact on both cropland and natural vegetation is not well understood yet, and collecting spatial and structural information around agroforestry systems is becoming an important issue. Tree mapping in semi-arid parklands could be one of these prerequisites. While for obtaining an exhaustive inventory of individual trees and for analysing their spatial distribution, remote sensing is the ideal tool. However, it has been noted that depending on the spatial resolution and sensor spectral characteristics, tree species cannot be distinguished clearly, even in the sparsely vegetated semi-arid ecosystems of West Africa. Thus, this work focuses on assessing the capabilities of Worldview-3 imagery, acquired in 8 spectral bands, to detect, delineate, and identify certain key tree species in the Faidherbia albida parkland in Bambey, Senegal, based on a ground-truth database corresponding to 5000 trees. The tree crowns are delineated through NDVI thresholding and consecutive filtering to provide object-based radiometric signatures, radiometric indices, and textural information. A factorial discriminant analysis is then performed, which indicates that only four out of the seven most abundant species in the study area can be discriminated: “Faidherbia albida”,” Azadirachta indica”, “Balanites aegyptiaca” and “Tamarindus indica”. Next, random forest and support vector machine classifiers are employed to identify the optimal combination of classifier parameters to discriminate these classes with a high accuracy, robustness, and stability. The linear support vector machine with cost=1 and gamma=0.01 provides the optimal results with a global accuracy of 88 % and kappa of 0.71. This classifier is applied to the whole study area to map all the trees with crowns larger than 2 m, sorted in four identified species and a fifth common group of unidentified species. This map thus enables analysing the variability in tree density and the spatial distribution of different species. Such information can afterwards be correlated to the ecological functioning of the parkland and local practices, and offers promising opportunities to help future sustainability initiatives in different socio-ecological contexts.  相似文献   

基于珞珈一号夜间灯光数据的广州市建设用地识别     

李翔  朱江  尹向东  姚江春  黄嘉玲  李密滔 《地球信息科学学报》2019,21(11):1802-1810

夜间灯光数据和人类活动密切相关,可用于识别城市建设用地。目前主要利用DMSP/OLS和NPP-VIIRS夜间灯光数据进行建设用地识别,由于数据质量原因,这两类数据的识别结果精度较差。珞珈一号夜间灯光数据与比以往夜间灯光数据相比,时间分辨率、空间分辨率和光谱分辨率明显提升,是进行建设用地提取的更理想的数据源。本研究首先对珞珈一号夜间灯光数据进行辐射和影像配准,提高数据质量,然后利用支持向量机(Support Vector Machine, SVM)影像分类方法对广州市2017 年建设用地分区识别,并利用Kappa系数分区、分地类评价识别结果精度。研究发现：① 利用珞珈一号夜间灯光数据识别建设用地的精度明显优于利用DMSP/OLS和NPP-VIIRS夜间灯光数据识别结果的精度;② 广州市中心城区辖区的建设用地识别结果精度较高,识别结果Kappa系数均在0.9以上;外围辖区识别结果精度相对较低,识别结果Kappa系数为0.85左右;③ 城市、建制镇等单个地块面积较大、灯光亮度较高的地类识别结果精度较高,识别结果Kappa系数均在0.9以上;村庄用地、铁路公路用地由于单个地块面积小、布局比较分散、部分路段无照明条件等原因,识别结果Kappa系数相对较低,为0.85左右;采矿、风景及特殊用地夜间基本无人类活动,缺少夜间灯光,难以用夜间灯光数据识别,Kappa系数为0.45左右。本研究证明了利用珞珈一号夜间灯光数据能有效识别建设用地,同时丰富了珞珈一号夜间灯光数据的应用场景。  相似文献   

Margin-based feature selection for hyperspectral data     

Mahesh Pal 《International Journal of Applied Earth Observation and Geoinformation》2009

A margin-based feature selection approach is explored for hyperspectral data. This approach is based on measuring the confidence of a classifier when making predictions on a test data. Greedy feature flip and iterative search algorithms, which attempts to maximise the margin-based evaluation functions, were used in the present study. Evaluation functions use linear, zero–one and sigmoid utility functions where a utility function controls the contribution of each margin term to the overall score. The results obtained by margin-based feature selection technique were compared to a support vector machine-based recurring feature elimination approach. Two different hyperspectral data sets, one consisting of 65 bands (DAIS data) and other with 185 bands (AVIRIS data) were used. With digital airborne imaging spectrometer (DAIS) data, the classification accuracy by greedy feature flip algorithm and sigmoid utility function was 93.02% using a total of 24 selected features in comparison to an accuracy of 91.76% with full set of 65 features. The results suggest a significant increase in classification accuracy with 24 selected features. The classification accuracy (93.4%) achieved by the iterative search margin-based algorithm with 20 selected features using sigmoid utility function is also significantly more accurate than that achieved with 65 features. To judge the usefulness of margin-based feature selection approaches, another hyperspectral data set consisting of 185 features was used. A total of 65 selected features were used to evaluate the performance of margin-based feature selection approach. The results suggest a significantly improved performance by greedy feature flip-based feature selection technique with this data set also. This study also suggest that margin-based feature selection algorithms provide a comparable performance to support vector machine-based recurring feature elimination approach.  相似文献   

地下水观测数据拟合与预测的支持向量机方法     

王炜  赵利飞  吴耿锋  马钦忠  林命啁 《地震》2007,27(1):9-16

影响地下水位变化因素有很多,在正常情况下,地下水位的变化实际上反应了气压、固体潮和降雨这些因素的变化,但是这些影响因子与地下水位之间有着较强的非线性关系。该文使用支持向量机方法建立起崇明中学观测站地下水位与气压、固体潮和降雨这些因素之间的非线性关系模型,并用于地下水观测数据拟合与预测,得到了较理想的结果,明显优于逐步回归方法。研究结果表明,支持向量机方法在地震前兆数据处理中有着广泛的应用前景。文中还对支持向量机方法在实际应用中的有关问题进行了讨论。  相似文献   

基于GIS的空间数据和空间数据库浅谈   总被引：4，自引：0，他引：4  

肖寒  吴侃  孙君 《江苏地质》2005,29(2):105-107

在数字城市、数字省区等数字工程建设和各个部门信息化建设迅速开展的时候，大量甚至海量空间数据的存储和管理成为地理信息系统建设工作者们面临的重要问题，研究空间数据和空间数据库变得非常迫切。简要介绍了空间数据的概念、特征和空间数据结构模型，并对空间数据库的设计做了简单阐述。  相似文献