Non-linear methods in remotely sensed multispectral data classification

The aim of this research is to develop an effective approach being able to deal with the stochastic nature of remote sensing data. In order to achieve this objective it is necessary to structure the methodological knowledge in the area of data mining and reveal the most suitable methods for the prediction and decision support based on large amounts of multispectral data. The idea is to establish a framework by decomposing the task into functionality objectives and to allow the end-user to experiment with a set of classification methods and select the best methods for specific applications. As a first step, we compare our results from Bayesian classification based on non-parametric probability density estimates of the data to the results obtained from other classification methods. Tree scenarios are considered, making use of a small benchmark dataset, a larger dataset from Corine land cover project for Bulgaria and analyzing different features and feature selection methods. We show that the theoretically optimal Bayesian classification can also achieve optimal classification in practice and provides a realistic interpretation of the world where land cover classes intergrade gradually.     

基于球体描述Vague决策的模拟电路故障诊断方法(英文)

提出一种基于球体描述Vague决策的模拟电路故障诊断方法。首先,采用小波变换预处理待测电路输出的电压故障特征。然后,每类样本集训练成一个最小超球体。最后,测试样本由本文定义的模糊决策规则进行判断,其中该规则由测试样本和描述球体中心之间的Vague加权距离得到。该模糊决策规则融合了测试样本正反隶属度值和描述球体的权值,可以有效地处理不确定信息。本文从理论上证明了该决策方法的可靠性。将该诊断方法应用于两种实际电路的测试,并与其他两种诊断方法进行对比。实验结果表明本文方法取得了良好的诊断性能,并减少诊断时间。     

飞翼无人机结构布局分级优化研究

针对传统结构设计中依据经验对机翼构件布局设计容易导致结构刚度偏大、重量偏大的问题,采用分离设计变量的方法,分别对机翼构件的尺寸和位置变量,采用改进的可行性方向法和Hook-Jeeves方法进行优化,将尺寸非线性优化嵌入到无约束位置优化中,以结构的刚度、位移、扭转和强度为约束条件,对布局进行调整.采用多学科框架软件对整个优化过程进行集成,将机翼结构重量作为目标函数,分级对位置和尺寸优化,充分考虑耦合位置和尺寸变量间的相互影响关系,循环迭代,直至得到结构重量的最优值.采用方法对某型飞翼无人机的机翼结构进行优化,结果合理,具有一定的工程应用价值.     

Temporal variation and asymmetry of sunspot and solar plage types from 1930 to 1936

Using the recently converted to digital format heliophysics catalogues of the Ebro Observatory published in the 1930s, we analyse simultaneously the temporal variation and asymmetry of two different solar structures located at different layers of the solar atmosphere: sunspots and solar plages. In particular, we do the research for all the types of sunspots and plages, including the daily and relative frequencies over the solar cycle. The data were catalogued using the sunspot Cortie classification and a solar plage classification scheme proposed by the Ebro Observatory, which group the phenomena by size and shape. For all types of both sunspots and plages, we observe a decrease in their frequency up to the end of solar cycle 16 and an increase over the beginning of solar cycle 17. Furthermore, we note that small sunspot groups are more likely to happen than bigger groups, although single big spots dominate near the solar minimum. The daily frequency of solar plage occurrences shows that there is not a dominance of compact or scattered solar plages. The North-South occurrence distribution of every type in both sunspots and solar plages shows an asymmetry during the solar cycle: in its declining phase, such asymmetry is directed to the north, while in the beginning of a new cycle is directed to the south.     

Development and testing of a statistical texture model for land cover classification of the Black Sea region with MODIS imagery

A statistical model is proposed for analysis of the texture of land cover types for global and regional land cover classification by using texture features extracted by multiresolution image analysis techniques. It consists of four novel indices representing second-order texture, which are calculated after wavelet decomposition of an image and after texture extraction by a new approach that makes use of a four-pixel texture unit. The model was applied to four satellite images of the Black Sea region, obtained by Terra/MODIS and Aqua/MODIS at different spatial resolution. In single texture classification experiments, we used 15 subimages (50 × 50 pixels) of the selected classes of land covers that are present in the satellite images studied. These subimages were subjected to one-level and two-level decompositions by using orthonormal spline and Gabor-like spline wavelets. The texture indices were calculated and used as feature vectors in the supervised classification system with neural networks. The testing of the model was based on the use of two kinds of widely accepted statistical texture quantities: five texture features determined by the co-occurrence matrix (angular second moment, contrast, correlation, inverse difference moment, entropy), and four statistical texture features determined after the wavelet transformation (mean, standard deviation, energy, entropy). The supervised neural network classification was performed and the discrimination ability of the proposed texture indices was found comparable with that for the sets of five GLCM texture features and four wavelet-based texture features. The results obtained from the neural network classifier showed that the proposed texture model yielded an accuracy of 92.86% on average after orthonormal wavelet decomposition and 100% after Gabor-like wavelet decomposition for texture classification of the examined land cover types on satellite images.     

基于共享最近邻的专利自动分类技术研究

专利文献是一种具有法律效力的科技文献,其内容覆盖了几乎所有的技术领域的最新、最活跃的创新技术信息,因此对专利文献的分类和组织在专利管理中有着重要意义。本文通过对现有的专利自动分类技术的归纳和分析,融合BM25相似度计算方法和样本邻域信息提出一种基于共享最近邻的KNN专利自动分类方法。本方法的有效性在NTCIR-8专利分类评测任务中得到充分验证。     

基于最小距离法的遥感图像分类

本文在ENVI遥感图像分析软件环境下,利用最小距离法对遥感图像进行了有监督分类。仿真实验通过对遥感图像中地物目标的光谱信息和空间信息进行分析及特征提取,利用判别函数计算到中心的距离,解读遥感图像,并对分类结果进行定量评估。实验结果表明用最小距离法来分析遥感图像可以获得较高精确度。     

基于经验学习的空间机器人精细抓捕方法

机器人在空间环境下完成对复杂形状物体的精细操作,要求其具有较强的自主操作规划能力.从学习人类经验出发,模仿人类经验生成来建立经验数据库,提出有效的物体分类方法,在物体类别基础上,识别同类物体的可抓取区域,并提出“单拇指”姿态规划方法,将对物体的操作经验泛化到同类物体的操作规划中.试验证明了算法的有效性.     

小行星与陨石的光谱联系

Bus-DeMeo光谱分类系统中有24种小行星光谱类型以及约27种陨石矿物学类型。小行星和陨石之间的光谱联系在质量和可靠性上差异很大原因主要是某些矿物学中缺乏诊断特征和空间风化作用。将回顾从可见光和近红外光谱中远程获取的小行星矿物学信息,讨论如何从地质学家的角度理解小行星的光谱辨识。     

二氧化碳探测仪瞬态热分析模型修正

为实现碳卫星载荷在轨温度的准确预测,对其试验状态瞬态热分析模型的修正进行研究。先比较热分析计算结果与热平衡试验结果,求出两者对应温度监控点的温差;再利用蒙特卡洛法对二氧化碳探测仪热分析模型参数进行灵敏性分类,将模型参数分为整体灵敏、局部灵敏与不灵敏参数。然后根据热平衡试验数据,用拉丁超立方和单纯形法的混合法对模型各个参数进行分层修正,得到满足目标函数各个灵敏性参数的最优值。最后将参数最优值代入热分析模型计算验证该修正方法正确性,并进行残差分析。结果显示修正后各温度监控点热分析计算与热试验温差δ_a小于±0.5℃,残差修正率θ高于80%,修正后多数温差比修正前减少了一个数量级。结果表明修正取得的效果明显,修正方法合理可行。