1) Support Vector Data Description-Similarity Reduction
支持向量数据约减算法
2) support vector data description
支持向量数据描述法
1.
The application of support vector data description for the fault prewarning of Power transformer;
支持向量数据描述法在变压器故障预警中的应用
2.
Due to the ART2 network getting dynamic modifying feature curve and accuration of support vector data description,the cleaning model has the function of dynamic cleaning for bad electric data.
电力负荷预测前应首先对负荷数据进行清洗,根据电力日负荷曲线的特征,应用改进的ART-2神经网络准确的提取电力日负荷特征曲线,然后利用支持向量数据描述法对不良数据进行精确定位,最后利用特征曲线对不良数据进行修正。
3) support vector machine
支持向量机算法
1.
A newly proposed technique of data mining, called "support vector machine" , is suitable for the data mining of ill-posed.
近年来新提出的“支持向量机算法”适合于处理不适定问题,能限制过拟合,且因采用核函数算法,能有效处理非线性数据集,与当前化学化工中应用极广的人工神经网络相比,优越性明显,在化学化工中具有巨大的应用潜力。
2.
And the data of Al, Ca, Cu, Zn, Mg contents have been processed by a new data mining algorithm, support vector machine proposed by Vapnik, in order to search the correlation between these data and high blood pressure disease.
计算表明:支持向量机算法建模的正确分类率和留一法预报正确率均较Fisher法和KNN法等传统的模式识别算法高。
3.
By using leaving-one method, it has been found that the prediction ability of the mathematical modei made by support vector machine is better than that made by Fisher method or KNN method.
本工作应用支持向量机算法总结实验数据的数学模型,并用留一法检验模型的预报能力。
4) support vector data description(SVDD)
支持向量数据描述
1.
In this paper,a support vector novelty detection algorithm,the support vector data description(SVDD), was adopted to represent known fault class samples,and to detect new fault class samples.
采用一种支持向量异常检测算法,即支持向量数据描述(SVDD),建立已知故障类训练样本的描述模型,并用于检测新的训练中未见的故障类样本。
2.
One-class support vector machine(OCSVM)and support vector data description(SVDD)are two main domain-based one-class(kernel)classifiers.
单类支持向量机和支持向量数据描述是两种流行的基于支撑域的单分类器。
3.
A method of malfunction diagnosis based on Empirical Mode Decomposition(EMD) and Support Vector Data Description(SVDD) is proposed to solve the problem of lacking malfunction smaples in Chongqing light-rail’s cast steel pedestal system diagnosis.
针对重庆轻轨铸钢支座系统故障诊断中缺乏故障样本的问题,提出一种基于经验模态分解(EMD)和支持向量数据描述(SVDD)的故障诊断方法。
5) SVDD
支持向量数据描述
1.
In view of the lack of fault samples,the technique of one-class classification-support vector data description(SVDD) is adopted for abnormal sound detection,in which the normal and abnormal conditions can be distinguished by one-class classifier,set up only on the base of samples in normal conditions.
针对驱动桥异响检测缺乏故障样本的问题,提出了异响检测的单值分类法———支持向量数据描述法(SVDD)。
2.
A c-SVDD algorithm is proposed based on Support Vector Date Description algorithm.
在基于解决单类问题的支持向量数据描述算法基础上提出了基于聚类分布信息的c-SVDD算法。
3.
By employing training examples of target set only, data description is able to obtain description of target set, and SVDD(support vector data description) is an efficient data description scheme.
数据描述只使用目标集训练样本获得关于目标集的描述,支持向量数据描述(SVDD)是一种有效的数据描述方法。
补充资料：支持向量机方法
支持向量机(SVM)是90年代中期发展起来的基于统计学习理论的一种机器学习方法，通过寻求结构化风险最小来提高学习机泛化能力，实现经验风险和置信范围的最小化，从而达到在统计样本量较少的情况下，亦能获得良好统计规律的目的。支持向量机算法是一个凸二次优化问题,能够保证找到的极值解就是全局最优解，是神经网络领域域取得的一项重大突破。与神经网络相比，它的优点是训练算法中不存在局部极小值问题，可以自动设计模型复杂度(例如隐层节点数)，不存在维数灾难问题，泛化能力强。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条