Time Series Prediction Based on Incremental Pruning Least Square Support Vector Machine 增量式剪枝最小二乘支持向量机的时间序列预测
Audio Clip Recognition and Retrieval Based on Incremental Learning with Support Vector Machine 基于增量学习支持向量机的音频例子识别与检索
An incremental learning algorithm based on support vector machine was proposed to process large scale data or data generated in batches. 为了扩展支持向量机在大规模数据集和成批出现数据领域的应用,提出了一种基于支持向量机的增量式学习算法。
To improve the face recognition rate, this paper proposes an incremental learning support vector machine ( SVM) face recognition scheme to update the parameters of SVM efficiently. 为了提高人脸识别率,本文提出了一种增量学习支持矢量机(SVM)人脸识别方法,有效地对SVM的参数进行更新。
Forecast Warning Level of Flight Delays Based on Incremental Ranking Support Vector Machine 基于增量式排列支持向量机的机场航班延误预警
A new geometric fast incremental learning algorithm for support vector machines ( SVM) was proposed. 提出了一种新的基于壳向量的增量式支持向量机快速学习算法。
An incremental training method for support vector machine is proposed to alleviate the computing burden of large-scale, high-dimension samples in multi-component gas analyzing. 针对大规模高维气体分析样本难以计算的问题,提出一种提升的支持向量机学习方法。
A Fast Iteration Algorithm Suitable for Incremental Learning for Training Support Vector Machine 一种适合于增量学习的支持向量机的快速循环算法
An incremental learning algorithm using multiple support vector machines ( SVMs) is proposed. 给出了使用多支持向量机进行增量学习的算法。
A Algorithm to Incremental Learning with Support Vector Machine and Its Application in Multi-class Classification 支持向量机的增量学习算法及其在多类分类问题中的应用
This thesis studies the incremental training algorithm of support vector machine ( SVM) and its application in process control. 本论文主要研究了支持向量机(supportVectorMachine,简称SVM)增量型训练算法及其在控制领域中的应用。
Incremental learning with support vector regression for pitch-controlled wind turbine online identification 基于SVR增量学习算法的变桨距风力机系统在线辨识
A Fast Incremental Learning Algorithm for Support Vector Machine 一种快速支持向量机增量学习算法
Incremental nonlinear proximal support vector classifier for multi-class classification based on Gaussian ker-nel is deduced. 在以往工作的基础上对近轴支持向量机进行了研究,推导了基于高斯核函数的非线性近轴支持向量机的增量式算法。
Incremental Regressive Learning Algorithm of Support Vector Machine 增量回归支持向量机改进学习算法
Multi-class Incremental Learning Based on Support Vector Machines 基于支持向量机的多分类增量学习算法
In order to extend common incremental learning algorithms into a parallel computation setting, an incremental learning algorithm with multiple support vector machine classifiers is proposed. 为了将一般增量学习算法扩展到并行计算环境中,提出一种基于多支持向量机分类器的增量学习算法。
Incremental support vector machine based on center distance ratio 基于中心距离比值的增量支持向量机
This paper presents a detection system for anomaly intrusion based on incremental support vector approach. The authors use normal Windows registry data set to train a detection model on a windows host, and employ SVM algorithm to detect abnormal registry access at run-time. 提出一种基于增量支持向量机的异常检测方法,利用Windows注册表建立了入侵检测模型,通过SVM算法实时判断当前对注册表的访问行为是否为异常状态来发现和识别入侵行为。
Fast incremental weighted support vector machines for predicating stock index 快速增量加权支持向量机预测证券指数
There is no incremental learning ability for the traditional support vector machine and there are all kinds of merits and flaws for usually used incremental learning method. Based on fixed partition and exceeding margin technique, an incremental learning algorithm using multiple support vector machines is presented. 传统的支持向量机不具有增量学习性能,而常用的增量学习方法各具有不同的优缺点,基于固定划分和过间隔技术,提出了使用多支持向量机进行增量学习的算法;
To combine the attribute reduction algorithm and the incremental training algorithm of support vector machine, a support vector machine classifier based on rough set is constructed. 将属性约简算法和支持向量机增量训练算法相结合,构造基于粗糙集数据预处理的支持向量机分类器。
Beginning with the architecture and key technologies for progressive transmission of vector spatial data, this thesis focuses on the research on simplification algorithms and incremental storage model of vector spatial data. 本文从矢量空间数据渐进传输的体系结构和关键技术出发,对矢量空间数据的化简算法及增量存储模型进行了重点研究。
Furthermore, for low updating efficiency of RBF network, Incremental Independent Vector Combination Predicting algorithm in Kernel Space is proposed and has lower computation complexity. 此外,针对RBF神经网络实时更新慢的缺点,本文在各个IMF分量预测建模中提出增量核空间独立向量组合预测算法,该算法的计算复杂度低。
This paper studies the incremental learning algorithm of support vector machine ( SVM). The Statistical Learning Theory ( SLT) is a new technique for solving various machine learning problems and shows that it is suitable for the finite data. 本文主要研究了支持向量机(supportVectorMachine,简称SVM)的增量学习算法。统计学习理论是机器学习领域的一个新的理论体系,它非常适用于解决有限样本下的机器学习问题。
Based on analysing and researching KKT conditions, found that the sample of violating the KKT in the incremental sample will change the initial support vector sample, and the initial not support vector sample maybe translate into support vector sample. 在深入分析和研究KKT条件的基础上,发现新增样本集中如果存在违反KKT条件的样本,必然会使原支持向量集发生变化,原非支持向量也有可能转化为支持向量。
After analyzing the domestic and abroad research about incremental updating, a set of incremental updating methods for vector land cover database is proposed in this paper. 本文在分析了国内外有关增量更新研究进展的基础上,提出了一套矢量地表覆盖数据增量更新处理方案。
The thesis chooses support vector machine as a classifier of image semantics, and studies classification performances of support vector machine on different feature subsets. The experiment result shows that the feature selection is effective and the incremental learning based on support vector machine is significant in application. 论文选择支持向量机作为图像语义的分类器,研究了不同特征子集下支持向量机的分类性能,实验结果证实了特征选择的有效性。
Though classical or standard SVM algorithm does not have incremental learning ability, its theoretical system of support vector concept is great significant to incremental learning construction. 经典的SVM算法并不直接具有增量学习的能力,但其理论体系中的支持向量概念对于增量学习算法的构建具有十分重要的意义。
With the high speed of economic and social development in China, the contradiction that the timeliness of incremental vector data ( as topographic map) is lagged far behind is breaking out day by day. 随着我国经济社会快速发展,地形图等矢量要素数据的时效性滞后于发展变化的矛盾日益突出。