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排序方式: 共有316条查询结果,搜索用时 15 毫秒
111.
太阳活动区是太阳大气中产生各种活动现象的区域,精确地检测和识别太阳活动区对理解太阳磁场的形成机制具有极为重要的科学意义.根据太阳活动区结构较为复杂的特点,基于尺度不变特征变换(ScaleInvariant Feature Transform, SIFT)和密度峰值聚类(Clustering by Fast Search and Find of Density Peaks,DPC)算法的优越性,提出了一种太阳活动区的自动检测和识别方法.首先,对太阳动力学天文台(Solar Dynamics Observatory, SDO)日震和磁场成像仪(Helioseismic and Magnetic Imager, HMI)的纵向磁图进行对比度增强;然后采用SIFT方法提取出全日面磁图中的特征点;最后利用DPC算法将特征点进行聚类,从而自动检测和识别出太阳活动区.研究结果表明, SIFT和DPC算法相结合的方法可以在不需要人工交互的情况下准确地自动检测出太阳活动区. 相似文献
112.
介绍了全套管旋挖钻进技术应用范围,并论述了几种不同形式的旋挖全套管钻进用设备及工法、套管的结构性能以及其相应的施工工艺。 相似文献
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114.
Data-driven topo-climatic mapping with machine learning methods 总被引:1,自引:1,他引:0
Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks. 相似文献
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116.
This paper proposes robust methods for local planar surface fitting in 3D laser scanning data. Searching through the literature revealed that many authors frequently used Least Squares (LS) and Principal Component Analysis (PCA) for point cloud processing without any treatment of outliers. It is known that LS and PCA are sensitive to outliers and can give inconsistent and misleading estimates. RANdom SAmple Consensus (RANSAC) is one of the most well-known robust methods used for model fitting when noise and/or outliers are present. We concentrate on the recently introduced Deterministic Minimum Covariance Determinant estimator and robust PCA, and propose two variants of statistically robust algorithms for fitting planar surfaces to 3D laser scanning point cloud data. The performance of the proposed robust methods is demonstrated by qualitative and quantitative analysis through several synthetic and mobile laser scanning 3D data sets for different applications. Using simulated data, and comparisons with LS, PCA, RANSAC, variants of RANSAC and other robust statistical methods, we demonstrate that the new algorithms are significantly more efficient, faster, and produce more accurate fits and robust local statistics (e.g. surface normals), necessary for many point cloud processing tasks. Consider one example data set used consisting of 100 points with 20% outliers representing a plane. The proposed methods called DetRD-PCA and DetRPCA, produce bias angles (angle between the fitted planes with and without outliers) of 0.20° and 0.24° respectively, whereas LS, PCA and RANSAC produce worse bias angles of 52.49°, 39.55° and 0.79° respectively. In terms of speed, DetRD-PCA takes 0.033 s on average for fitting a plane, which is approximately 6.5, 25.4 and 25.8 times faster than RANSAC, and two other robust statistical methods, respectively. The estimated robust surface normals and curvatures from the new methods have been used for plane fitting, sharp feature preservation and segmentation in 3D point clouds obtained from laser scanners. The results are significantly better and more efficiently computed than those obtained by existing methods. 相似文献
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118.
GIS的分层与特征的数据组织模式 总被引:4,自引:0,他引:4
数据组织是 GIS系统建设的基础和前提 ,认知方式、认知手段的变化 ,会带来认知结果的不同 ,形成了两种不同的数据组织方法 :(1 )基于分层的数据组织方法 ;(2 )基于特征的数据组织方法。文章分析了这两种数据组织方法的有关内容 ,并对它们进行了对比 ,认为基于特征的数据组织方法是第 4代 GIS的基础和核心 ,是 GIS的发展方向。 相似文献
119.
实现遥感影像的2维可视化动态漫游则可以从不同的视角以不同的速度对地面信息进行观察,以实现重复再现和分析的效果。实现漫游首先要从遥感影像中提取特定的地理信息,并对特定投影的遥感影像进行坐标转换后逐帧绘制。本文利用对UTM投影的GeoTIFF卫星像片进行3维坐标转换,并实现第一和第三人称的3维漫游。 相似文献
120.
对新疆塔里木河流域进行土地盐渍化专题信息提取,建立该地区土地盐渍化分类系统,提高土地盐渍化分类精度。结果表明:所采用的土地盐渍化专题信息提取方法是可行的,对于生态环境监测的土地利用/覆盖、土壤沙漠化等问题均适用。对于建立生态环境监测系统有非常实用的价值。 相似文献