排序方式: 共有22条查询结果,搜索用时 15 毫秒
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高维遥感图像的快速分类算法 总被引:1,自引:0,他引:1
为了实现对高维遥感图像的快速准确分类,提出了一种基于k均值二叉树支持向量机(SVM)的分类方法。该方法通过对选取的训练样本进行k均值聚类,生成支持向量机分类二叉树,作为确定最佳分类顺序的依据,以降低分类过程中的误差累积并提高整体分类精度,而且可缓解由样本数量不均衡导致的分类误差。该方法可在不进行降维处理的情况下,对高维遥感图像进行快速准确分类。测试结果表明,其分类速度和分类精度都优于传统的支持向量机分类结果。 相似文献
2.
WiFi-PDR室内组合定位的无迹卡尔曼滤波算法 总被引:1,自引:0,他引:1
针对当前室内定位的应用需求和亟待解决的关键问题,结合城市室内环境下广泛存在的WiFi无线信号以及智能手机传感器信息,提出了一种WiFi无线信号联合行人航迹推算(PDR)的室内定位方法。该方法采用无迹卡尔曼滤波(UKF)算法对WiFi和PDR定位信息进行融合处理,有效克服了WiFi单点定位精度低和PDR存在累计误差的问题。针对融合算法中WiFi指纹匹配计算量大的问题,用k-means聚类算法对WiFi指纹库进行聚类处理,降低了指纹匹配算法的计算量,提高了算法的实时性。通过在华为P6-U06智能手机平台上实际测试,在时间效率上经过聚类处理后系统定位耗时有很大程度的改善,平均降幅为51%,其中最大降幅达到64%,最小的也达到了36%;在定位精度上,当室内人员为行走状态时WiFi定位平均误差为7.76m,PDR定位平均误差为4.57m,UKF滤波融合后平均定位误差下降到1.24m。 相似文献
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图像分类中基于核映射的光谱匹配度量方法 总被引:1,自引:0,他引:1
针对多光谱遥感数据特点利用SSV匹配技术改进高斯核函数得到新的KSSV函数,然后在由KSSV核函数映射得到的高维空间中利用SAM匹配技术代替基于欧氏距离的相似性度量。如此可以充分挖掘多光谱影像中的波谱特征信息并有效利用,提高模式识别方法应用的有效性。将此方法分别应用于非监督分类(k均值)与监督分类(最小距离、SVM)的试验表明,改进度量的分类方法可显著提高地类间的可区分度并有效降低类内的不一致性,更有效针对多光谱遥感影像中的地物类型,获得较好的精度改进。 相似文献
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澜沧江及周边流域TRMM3B43数据精度检验 总被引:19,自引:1,他引:18
在地形复杂的澜沧江及周边流域,利用相关系数法、散点斜率法,以研究区内35个国家基准与基本站观测数据为“真值”对1998-2009年之间月尺度的TRMM 3B43降水数据精度进行检验,采用泰森多边形法、K-Means聚类法分析了高程与坡度对检验结果的影响,借助主成分法比较了高程与坡度对TRMM 3B43的影响程度.研究表... 相似文献
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Isaiah Gwitira Amon Murwira Mhosisi Masocha Fadzai M. Zengeya Munyaradzi Davis Shekede Joconiah Chirenda 《国际地球制图》2013,28(11):1163-1176
AbstractMalaria burden has considerably declined in the last 15 years mainly due to large-scale vector control. The continued decline can be sustained through malaria risk stratification. Malaria stratification is the classification of geographical areas according to malaria risk. In this study, ecological niche modelling using the maximum entropy algorithm was applied to predict malaria vector habitat suitability in terms of bioclimatic and topographic variables. The output vector suitability map was integrated with malaria prevalence data in a GIS to stratify Zimbabwe into different malaria risk zones. Five improved and validated malaria risk zones were successfully delimited for Zimbabwe based on the World Health Organization classification scheme. These results suggest that the probability of occurrence of major vectors of malaria is a key determinant of malaria prevalence. The delimited malaria risk zones could be used by National Malaria Control programmes to plan and implement targeted malaria interventions based on vector control. 相似文献
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利用数据挖掘的滑坡监测数据处理流程 总被引:1,自引:0,他引:1
为有效处理海量、多种类的滑坡监测数据,提出了基于数据挖掘的滑坡监测数据处理流程。以白家包滑坡为例,利用k-means算法对监测数据进行定性处理,进而利用Apriori算法分析滑坡形变的诱发因素。实验结果表明,提出的流程能有效地处理滑坡监测数据,并发掘到有助于人们认识滑坡形变及其原因的知识。 相似文献
8.
Land subsidence induced by excessive groundwater withdrawal has caused serious social, geological, and environmental problems in Beijing. Rapid increases in population and economic development have aggravated the situation. Monitoring and prediction of ground settlement is important to mitigate these hazards. In this study, we combined persistent-scatterer interferometric synthetic aperture radar with Grey system theory to monitor and predict land subsidence in the Beijing plain. Land subsidence during 2003–2014 was determined based on 39 ENVISAT advanced synthetic aperture radar (ASAR) images and 27 RadarSat-2 images. Results were consistent with global positioning system, leveling measurements at the point level and TerraSAR-X subsidence maps at the regional level. The average deformation rate in the line-of-sight was from ?124 to 7 mm/year. To predict future subsidence, the time-series deformation was used to build a prediction model based on an improved Grey-Markov model (IGMM), which adapted the conventional GM(1,1) model by utilizing rolling mechanism and integrating a k-means clustering method in Markov-chain state interval partitioning. Evaluation of the IGMM at both point level and regional scale showed good accuracy (root-mean-square error <3 mm; R2 = 0.94 and 0.91). Finally, land subsidence in 2015–2016 was predicted, and the maximum cumulative deformation will reach 1717 mm by the end of 2016. The promising results indicate that this method can be used as an alternative to the conventional numerical and empirical models for short-term prediction when there is lack of detailed geological or hydraulic information. 相似文献
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AbstractHyLogger profile scanning is commonly utilised for drill-core logging but the limited scanning area may not detect all important geological features. The study presented in this paper aims to develop a mineral mapping solution for this core-logging process by leveraging the colour image captured during the scanning process. A machine-learning-based computer vision program was developed by implementing a k-means clustering and a global colour profiling algorithm. A suite of drill-core images was used to validate the developed program. Results indicate that there is a direct correlation between the mineral assemblage of a rock type and its colour specifications. The identified mineral type and relative abundance were comparable with HyLogger scan results. 相似文献
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Evaluation of graphical and multivariate statistical methods for classification of water chemistry data 总被引:12,自引:2,他引:12
Cüneyt Güler Geoffrey D. Thyne John E. McCray Keith A. Turner 《Hydrogeology Journal》2002,10(4):455-474
A robust classification scheme for partitioning water chemistry samples into homogeneous groups is an important tool for the
characterization of hydrologic systems. In this paper we test the performance of the many available graphical and statistical
methodologies used to classify water samples including: Collins bar diagram, pie diagram, Stiff pattern diagram, Schoeller
plot, Piper diagram, Q-mode hierarchical cluster analysis, K-means clustering, principal components analysis, and fuzzy k-means
clustering. All the methods are discussed and compared as to their ability to cluster, ease of use, and ease of interpretation.
In addition, several issues related to data preparation, database editing, data-gap filling, data screening, and data quality
assurance are discussed and a database construction methodology is presented.
The use of graphical techniques proved to have limitations compared with the multivariate methods for large data sets. Principal
components analysis is useful for data reduction and to assess the continuity/overlap of clusters or clustering/similarities
in the data. The most efficient grouping was achieved by statistical clustering techniques. However, these techniques do not
provide information on the chemistry of the statistical groups. The combination of graphical and statistical techniques provides
a consistent and objective means to classify large numbers of samples while retaining the ease of classic graphical presentations.
Electronic Publication 相似文献