基于多尺度动态模型的自适应跟踪算法

This paper simply introduces multi-scale analysis and target-tracking theory, presents a better solution for Px(t), with theoretical proof of the solution's correctness. Based on multi-scale analytical idea, combing the dynamic system analysis of movement model with wavelet transform method, this paper puts forward a multi-scale self-adap-tive fusion tracking algorithm,and gives the concrete implementing steps of this algorithm, with simulation experi-ment. In the simulation experiment, makes a comparison between the algorithm and the traditional single-scale track-ing method. And the theoretical proof and the experiment results prove the algorithm to be both feasible and effec-tive. This algorithm adjusts tracking scale automatically according the state of model target. And it also can use de-tective data effectively and more accurately portray the variation of track. It avoids the disadvantages of single scaleand realizes the tracking towards dynamic model. Comparing with the traditional single tracking method, this algo-rithm more fits the needs of target tracking and has practical value.     

一种视口相关的空间数据多尺度检索方法

合理高效的数据对象选择策略是提高分布式空间数据检索效率的重要因素之一。基于人眼视觉特性,综合考虑了视口尺度对分布式空间数据检索的影响,提出了一种视口尺度相关的分布式空问数据检索方法,将视口尺度集成到分布式空问数据对象选择算法中,能根据视口尺度自适应地调整分布式空间数据对象的选择策略。实验结果表明,谈方法在小视口尺度检索时能显著降低处理和传输的数据量,以较小代价快速得到查询结果的近似解。     

农业模型组件主题图的生成方法

分析农业模型的信息组织需求,提出一种农业模型组件主题图的生成方法,对模型组件的元数据信息进行XTM标注,形成属性元主题图。利用实例化和反射技术,生成具体模型组件的局部原子主题图。通过主题信息的字符匹配算法,融合同类模型的原子主题图,形成农业模型组件的全局原子主题图。以作物生育期模型组件的主题图为实例,验证了该方法的有效性。     

A generalized greedy routing algorithm for 2-connected graphs

Geometric routing by using virtual locations is an elegant way for solving network routing problems. In its simplest form, greedy routing, a message is simply forwarded to a neighbor that is closer to the destination. One main drawback of this approach is that the coordinates of the virtual locations require Ω(nlogn) bits to represent, which makes this scheme infeasible in some applications.The essence of the geometric routing is the following: When an origin vertex u wants to send a message to a destination vertex w, it forwards the message to a neighbor t, solely based on the location information of u,w and all neighbors of u. In the greedy routing scheme, the decision is based on decreasing distance. For this idea to work, however, the decision needs not be based on decreasing distance. As long as the decision is made locally, this scheme will work fine.In this paper, we introduce a version of greedy routing which we call generalized greedy routing algorithm. Instead of relying on decreasing distance, a generalized greedy routing algorithm uses other criteria to determine routing paths, solely based on local information. We present simple generalized greedy routing algorithms based on st-coordinates (consisting of two integers between 0 and n−1), which are derived from an st-orientation of a 2-connected plane graph. We also generalize this result to arbitrary trees. Both algorithms are natural and simple to be implemented.     

Blowing Bubbles for Multi-Scale Analysis and Decomposition of Triangle Meshes

Tools for the automatic decomposition of a surface into shape features will facilitate the editing, matching, texturing, morphing, compression and simplification of three-dimensional shapes. Different features, such as flats, limbs, tips, pits and various blending shapes that transition between them, may be characterized in terms of local curvature and other differential properties of the surface or in terms of a global skeletal organization of the volume it encloses. Unfortunately, both solutions are extremely sensitive to small perturbations in surface smoothness and to quantization effects when they operate on triangulated surfaces. Thus, we propose a multi-resolution approach, which not only estimates the curvature of a vertex over neighborhoods of variable size, but also takes into account the topology of the surface in that neighborhood. Our approach is based on blowing a spherical bubble at each vertex and studying how the intersection of that bubble with the surface evolves. We describe an efficient approach for computing these characteristics for a sampled set of bubble radii and for using them to identify features, based on easily formulated filters, that may capture the needs of a particular application.     

基于聚类的字典压缩技术在GIS中的应用研究

本文主要探讨了基于字典的矢量地图压缩中字典的设计问题,提出了一种新颖的基于聚类方式的字典设计方法,它可以使字典更好的近似于某种特定的数据集。实验证明只要字典结构适合,这种基于聚类方式的字典数据压缩技术可获得更好的压缩效果。     

HSC: A multi-resolution clustering strategy in Self-Organizing Maps applied to astronomical observations

This work presents a strategy for the classification of astronomical objects based on spectrophotometric data and the use of unsupervised neural networks and statistical classification algorithms. Our strategy constitutes an essential part of the preparation phase of the automatic classification and parameterization algorithms for the data that are to be collected by the Gaia satellite of the European Space Agency (ESA), whose launch is foreseen for the spring of 2012. The proposed algorithm is based on a hierarchical structure of neural networks composed of various tree-structured SOM networks. The classification of possible astronomical objects (stars, galaxies, quasars, multiple objects, etc.) basically consists in the iterative segmentation of the inputs space and the ensuing generation of initial classifications and increase in classification precision by means of a refining process. Apart from providing a classification, our technique also measures the quality and precision of the classifications and segments the objects for which it cannot determine whether or not they belong to a pre-established class of astronomical objects (outliers).     

一种新的地形图汉字注记自动提取算法

地形图中包含大量的汉字注记,为了实现地图要素自动识别,首先要将文字正确地提取出来。该文通过对汉字特征的分析,提出了一种新的汉字提取算法。首先根据地图图像的特点进行骨架运算,利用形态算子对汉字笔画进行分解,最后实现对汉字注记的笔画统计提取。该算法较好地解决了字线粘连、旋转等情况下的汉字提取问题,具有良好的稳定性。     

一种新的数字化三维Baker映射扰动方案

提出了一种对数字化三维Baker混沌系统进行扰动的可行方案,该方案选择性扩散数字化混沌系统中的部分变量,以达到对整个系统的扰动。实验的数据表明,该扰动方案有效地补偿了多维数字化混沌系统的动力学特性退化。     

A*算法在矢量地图最优路径搜索中的应用

在交通地理信息系统应用中,如何既快速又准确地找到最优路径是一个关键的问题.将人工智能领域的A*算法引入到矢量地图的最优路径搜索中来,论述了应用于矢量地图最优路径搜索的A*算法是一种完备的算法.同时,针对交通矢量地图的特点,提出了一种将矢量地图本身节点的数据结构和A*算法需搜索的节点数据结构在索引时相互联系,在计算时又相互分离的策略,提高了A*算法的执行效率.实验表明这种改进数据结构的A*算法在准确性和快速性方面都取得了令人满意的效果.     

基于多尺度彩色形态矢量算子的边缘检测

数学形态学在图象处理中已经得到广泛地应用，但传统的形态学常应用于二值图象处理，后来发展应用到灰度图象处理，对于其用于彩色图象处理的研究还不是很多，通过对传统的数学形态学的几何描述，以及对目前形态学在边缘检测中的应用分析，提出了一种新的多尺度的彩色形态矢量边缘检测算子，该方法是利用不同尺度形态边缘检测算子来检测不同尺度下的边缘强度，再对不同尺度下的边缘强度图进行合并，从而得到新的边缘强度图象，利用该算法对实际图象和合成图象进行了实验，将实验结果与传统的边缘检测算法相比较，由于新的多尺度彩色形态矢量算子能检测出更多的细节边缘，因此将更有利于图象的进一步分析处理，同时将实验图象人为地增加噪声后，再利用该算法进行实验，其结果表明，该算法对噪声具有很好的鲁棒性。     

一种基于道路知识的矢量地图数据校正方法

准确完整的交通矢量地图是车辆导航、路径寻优等应用工作的良好基础.为了解决交通矢量地图的错误数据信息问题,在分析城市道路分布特点的基础上,提出了一种基于道路知识的矢量地图数据校正方法.将矢量数据信息中普遍存在的错误进行分类,通过对城市道路设计规范和城市道路相关知识的归纳,抽取出对各种类型错误的判定规则和校正算法,为矢量地图的校正提供了一种较新的思路.实验结果表明,该算法能够快速有效的检测和校正矢量地图数据信息中存在的各类问题,能够保证矢量地图拓扑的准确性和完整性.     

RNA二级结构预测的支持向量机模型研究

RNA二级结构预测问题是生物信息学的一个研究重点,本文主要利用支持向量机(SVM)模型来研究RNA 二级结构预测问题.通过改进NSSEL标签[4],形成了能表示平面伪结结构的E-NSSEL标签,该标签作为SVM模型输出端的类别标识,因此,测试序列经过SVM模型预测后得到相应的E-NSSEL序列,该序列可以恢复为二级结构.此算法能有效地解决传统算法中存在的时间复杂性的问题和长链分子的预测问题.     

基于多尺度稀疏LSSVM的时间序列预测

最小二乘支持向量机在提高了支持向量机的运算速度的同时,失去了解的稀疏性.构造的多尺度稀疏最小二乘支持向量机,首先通过小波包分解对于数据进行多尺度描述,同时采用最小二乘支持向量机的学习算法获得数据之间的尺度相关性,可以实现解的稀疏性和可解释性,从而实现了系统的多尺度分解、子系统建模与合成的一体化.通过在时间序列预测上的应用可以发现,此模型在获得稀疏解的同时,极大地提高了系统的性能.而且,可以获得输出结果在不同尺度上的贡献度,增加了系统的可解释性.     

矢量地图数字水印研究综述

矢量地图广泛应用于地理信息系统、军事测绘等领域.矢量地图数字水印为数字地图提供版权保护及防伪认证等功能,近几年其研究取得了较大的进展.为使人们对该领域研究现状有概要了解,首先论述了矢量地图水印的特性及评价准则;然后重点分析了空域、频域、零水印以及多重水印算法,并通过实验比较了几类算法的优缺点;最后提出了矢量地图数字水印的发展方向和研究目标.     

Web mining based on Growing Hierarchical Self-Organizing Maps: Analysis of a real citizen web portal

This work is focused on the usage analysis of a citizen web portal, Infoville XXI (http://www.infoville.es) by means of Self-Organizing Maps (SOM). In this paper, a variant of the classical SOM has been used, the so-called Growing Hierarchical SOM (GHSOM). The GHSOM is able to find an optimal architecture of the SOM in a few iterations. There are also other variants which allow to find an optimal architecture, but they tend to need a long time for training, especially in the case of complex data sets. Another relevant contribution of the paper is the new visualization of the patterns in the hierarchical structure. Results show that GHSOM is a powerful and versatile tool to extract relevant and straightforward knowledge from the vast amount of information involved in a real citizen web portal.     

基于多尺度分析的地基云图自动识别的研究

研究地基云图自动识别问题.地基云图由于受光照旋转等影响,传统方法提取的特征难以准确描述图像特征,导致地基云图识别的精度较低,还无法达到实际应用的要求.为了提高地基云图识别精度,提出采用多尺度分析的地基云图自动识别算法.首先将地基云图划分为若干个大小相同互不重叠的子图,然后采用三种不同尺度的权重局部二值模式提取每一幅子图的纹理特征,最后将子图的纹理特征顺序排列获取最终鉴别特征.通过对积雨云,高积云和层积云三类地基云图进行分类识别,实验结果表明改进方法可以增强云图的局部特征描述能力,有效提高地基云图分类的精度.     

一种基于CW-RNN的多时间尺度序列建模推荐算法

序列化推荐试图利用用户与物品的历史交互序列,预测下次即将交互的物品。针对序列化推荐中推荐物品依赖于用户的长时间全局兴趣、中时间兴趣还是短时间局部兴趣的不确定性,该文提出了一种基于CW-RNN的多时间尺度序列建模推荐算法。首先,该算法引入CW-RNN层,从用户与物品的历史交互序列中抽取多个时间尺度的用户兴趣特征。然后,通过尺度维卷积来建模对不同时间尺度的用户兴趣特征的依赖,生成多时间尺度用户兴趣特征的统一表示。最后,利用全连接层建模统一的多尺度用户兴趣特征和隐式物品特征的交互关系。在MovieLens-1M和Amazon Movies and TV两个公开数据集上的实验结果表明,相比于现有最优的序列推荐算法,该文提出的算法在准确率上分别提升了3.80%和8.63%。     

神经网络技术下多尺度时序数据离群点挖掘

在大量的网络数据中,可能隐藏着少许攻击序列,离群点是由异常机制产生,不服从数据的普遍分布规律,设计一个基于神经网络的多尺度时序数据离群点挖掘方法.采用对象与其类别聚类中心的相似度来测量对象属于聚类的程度,确定检测对象的邻域,采用神经网络技术对多尺度时序数据离群点挖掘,初始化BP神经网络,基于网络的实际输出和预期输出,判...     

一种基于整体拓扑结构的对地图中线对象的细化算法

本文针对传统细化算法国有的局限性，结合地图中线对象的特点，提出一种新的细化算法。该算法基于图段，通过确定节点位置及其相互间连接关系，从全局上把握图形拓扑结构。充分利用整体信息，无需细化选代，减少了运算量，同时很好地避免了交点略变现象。