SVG的3D实现

针对SVG在3D图形的描述与绘制上存在局限性的问题,提出了一种SVG的3D实现方法;详细介绍了SVG的2D坐标系到3D坐标系的转换原理,给出了转换到3D坐标系后的SVG-3D图形的绘制与操控流程,并以在3D场景中绘制一个正立方体和圆球体为例,介绍了在HTML页面中采用JavaScript创建3D场景和绘制与操控这2个图形的实现。     

A new ECG beat clustering method based on kernelized fuzzy c-means and hybrid ant colony optimization for continuous domains

The kernelized fuzzy c-means algorithm uses kernel methods to improve the clustering performance of the well known fuzzy c-means algorithm by mapping a given dataset into a higher dimensional space non-linearly. Thus, the newly obtained dataset is more likely to be linearly seprable. However, to further improve the clustering performance, an optimization method is required to overcome the drawbacks of the traditional algorithms such as, sensitivity to initialization, trapping into local minima and lack of prior knowledge for optimum paramaters of the kernel functions. In this paper, to overcome these drawbacks, a new clustering method based on kernelized fuzzy c-means algorithm and a recently proposed ant based optimization algorithm, hybrid ant colony optimization for continuous domains, is proposed. The proposed method is applied to a dataset which is obtained from MIT–BIH arrhythmia database. The dataset consists of six types of ECG beats including, Normal Beat (N), Premature Ventricular Contraction (PVC), Fusion of Ventricular and Normal Beat (F), Artrial Premature Beat (A), Right Bundle Branch Block Beat (R) and Fusion of Paced and Normal Beat (f). Four time domain features are extracted for each beat type and training and test sets are formed. After several experiments it is observed that the proposed method outperforms the traditional fuzzy c-means and kernelized fuzzy c-means algorithms.     

A refined evaluation of the gas-phase water-dimerization equilibrium constant within non-rigid BJH- and MCY-type potentials

The flexible BJH- and flexible or semiflexible MCY-type water-water potentials (4 potential modifications in each nonrigid family, i.e., altogether 12 potentials) are used for evaluation of the gas-phase water-dimerization equilibrium constants. The potential-energy term is adjusted for best reproduction of the available experimental equilibrium constants. An independent test using the experimental steam second-virial coefficient isotopic difference shows that the adjustment also improves the computational evaluation of the difference. A set of dimerization equilibrium constants is suggested over a wide temperature interval (based on the BJH/G, MCY-B, or MCYB potential modifications). The best reproduction of the experimental equilibrium constants (in conjunction with good performance for the second-virial isotopic difference) is produced by the BJH/G potential. The results are applicable to various problems such as the formation of water clusters in large-scale natural and artificial water jets (e.g., hydrogen-oxygen rocket motors, orbital capsule water dumps, water ejection from a comet nucleus) or in atmospheric chemistry.     

选择性集成算法分类与比较

选择性集成是当前机器学习领域的研究热点之一。由于选择性集成属于NP"难"问题,人们多利用启发式方法将选择性集成转化为其他问题来求得近似最优解,因为各种算法的出发点和描述角度各不相同,现有的大量选择性集成算法显得繁杂而没有规律。为便于研究人员迅速了解和应用本领域的最新进展,本文根据选择过程中核心策略的特征将选择性集成算法分为四类,即迭代优化法、排名法、分簇法、模式挖掘法;然后利用UCI数据库的20个常用数据集,从预测性能、选择时间、结果集成分类器大小三个方面对这些典型算法进行了实验比较;最后总结了各类方法的优缺点,并展望了选择性集成的未来研究重点。     

基于模糊数学的高维稀疏数据聚类统计方法设计

传统的数据聚类统计方法仅适用于低维数据聚类问题,为此,本研究设计了基于模糊数据的高维稀疏数据聚类统计方法,以期提升高维稀疏数据的聚类统计效果。以模糊C均值聚类算法为基础,通过优化初始聚类中心解决局部最优问题,缩短聚类统计时间;然后引入权重机制,令该方法适用于高维稀疏数据聚类统计。基于此,以余弦距离替换原有的欧几里德距离,提高高维稀疏数据聚类统计效果。实验证明：在数据维度不同时,该方法均有较优的聚类统计效果。当数据维度较低时,分块比例为10%时聚类统计效果最优;当数据维度较高时,分块比例为40%时聚类统计效果最优。在不同稀疏度等级时,该方法的命中率和聚类统计效率均较高。     

基于BC聚类的差分隐私保护推荐算法

为提高差分隐私保护下推荐算法的准确性,提出了一种考虑差分隐私保护的基于Bhattacharyya系数（BC）的聚类推荐算法.以BC作为项目相似性度量的标准,根据BC相似性对项目进行K-medoids聚类,并在聚类簇中进行私有项目邻居选择.最后,根据最近邻居集信息,对用户的评分进行预测和Top-n推荐.提出的方案有效地克服了已有方法中存在的相似性度量依赖于共同评分的问题,提高了相似性度量的准确性,有效避免了因隐私保护而造成的最近邻居集质量下降的问题.理论分析和实验测试的结果表明,该方法在实现隐私保护的同时还能有效保证推荐的高质量,较好地实现了隐私保护和数据效用之间的平衡,具有良好的应用潜力.     

高温混合障碍空间中的移动机器人路径规划

为了解决高温场景中移动机器人全局路径规划所面临的安全与效率问题,提出高温热源虚拟障碍的定义,建立混合障碍空间模型,将高温场景中的路径规划问题转化为高温混合障碍空间中考虑路径温度代价和长度代价的多目标优化问题. 改进NSGA-Ⅱ算法,通过选取优秀非可行解扩展种群,提高了种群多样性和进化效率,提出新的交叉和变异概率计算方法. 根据种群进化进程和个体代价函数值调整概率,实现了种群前期搜索能力和后期收敛性的平衡. 仿真所得的最优路径结果表明,该改进算法的路径长度代价虽然比原算法和其他改进算法略有增加,但温度代价大幅降低,更有效地避免了陷入局部最优.     

结晶器电偶温度数据预处理方法的研究

提出了一套热电偶温度数据预处理方案。将所提出的数据预处理方案应用于自行开发的基于RBF神经网络预报系统中，表明了该方案能有效降低误报率，同时也提高了预报精度。     

预测帧编码中基于场景信息的宏块模式跳过算法*

在对场景信息进行分析的基础上,提出了H.264/AVC中预测帧的一种快速算法.对于未发生场景切换的预测帧,采用INTRA模式跳过算法(IMSA),跳过该帧中所有的INTRA模式的决策过程.对于发生场景切换的预测帧,跳过INTER模式的决策过程(PMSA).仿真结果显示,与采用完整的率失真优化(RDO)决策过程相比,未发生场景切换时,所提方法能减少30%～60%的编码时间;发生场景切换时,能减少60%～70%的编码时间,并且未导致明显的图像质量下降和码率的增加.