1) least squares support vector machine
最小二乘支持向量机
1.
Application of least squares support vector machine within evidence framework in PTA process;
基于证据框架的最小二乘支持向量机在精对苯二甲酸生产中的应用
2.
Pressure sensor temperature compensation based on least squares support vector machine;
基于最小二乘支持向量机的压力传感器温度补偿
3.
Sparse least squares support vector machine;
稀疏最小二乘支持向量机
2) least square support vector machine
最小二乘支持向量机
1.
Forecast of water inrush from coal floor based on least square support vector machine;
基于最小二乘支持向量机的煤层底板突水量预测
2.
Outliers detection in time series of measured data based on least square support vector machine algorithm;
基于最小二乘支持向量机算法的测量数据时序异常检测方法
3.
Image registration based on least square support vector machine;
基于最小二乘支持向量机的图像配准研究
3) least squares support vector machines
最小二乘支持向量机
1.
Coal washery daily water consumption short-term prediction based on least squares support vector machines;
基于最小二乘支持向量机的选煤厂日用水量短期预测
2.
Selection of suitable 3D terrain matching field based on least squares support vector machines;
基于最小二乘支持向量机的三维地形匹配选择
3.
Thermal error prediction of numerical control machine tools based on least squares support vector machines;
基于最小二乘支持向量机的数控机床热误差预测
4) LS-SVM
最小二乘支持向量机
1.
Prediction of hydrogen content in molten aluminum based on LS-SVM;
利用最小二乘支持向量机预测铝熔体氢含量
2.
Time Series Prediction Based on LS-SVM;
基于最小二乘支持向量机的小样本建模方法研究
3.
Research on vibration fault diagnosis of hydro-turbine generating unit based on LS-SVM and information fusion technology;
基于最小二乘支持向量机和信息融合技术的水电机组振动故障诊断研究
5) least square support vector machines
最小二乘支持向量机
1.
Medium and long-term load forecasting based on rough sets and least square support vector machines;
基于粗糙集理论和最小二乘支持向量机的中长期负荷预测
2.
Fuzzy least square support vector machines for regression;
回归型模糊最小二乘支持向量机
3.
Prediction of chaotic time series using least square support vector machines;
混沌时间序列的最小二乘支持向量机预测
6) LSSVM
最小二乘支持向量机
1.
On sample data collected from real plant, the pretreatments are conducted by lapse-error-way, random-error-way and unitary-way with data statistic theory; On the basis of analysis of several methods for modeling, a soft sensor based on kernel principal component analysis(KPCA) and least square support vector machine(LSSVM) is proposed.
对现场采集的过程数据形成的样本集,应用数理统计方法对数据进行预处理:剔除异常数据、消除随机误差以及归一化;在具体分析了多种建模方法的基础上,提出了核主元分析结合最小二乘支持向量机软测量建模方法。
2.
The Least Square Support Vector Machine(LSSVM)is promoted by Support Vector Machine(SVM).
最小二乘支持向量机(Least Square Support Vector Machine,LSSVM)是基于支持向量机方法的一种改进算法。
3.
Firstly,adaptive weighted fusion and least square support vector machine(LSSVM) algorithms are designed.
首先给出了自适应加权融合和最小二乘支持向量机(LSSVM)算法,其次对三个非线性测试函数分别运用BP神经网络、LSSVM和基于自适应加权融合的LSSVM算法进行建模并比较了精度,最后给出了基于自适应加权融合的LSSVM在火电厂飞灰含碳量建模中应用的结果。
补充资料:乘扁舟
"乘扁舟"用来作功成身退之用。出自于《史记货殖列传》。
公元前498年,越王勾践出兵攻打吴国,贸然出兵,结果越军大败,狼狈而逃,被吴军围困在了会稽山上。范蠡建议勾践向吴国求和,以便积蓄力量,日后东山再起。勾践无奈,只好按范蠡的计策行事,范蠡随同勾践一同到吴国去做奴仆。他们在吴国备受屈辱,终于取得了吴王的信任,返回越国。勾践回国后,决心报仇雪耻,他一方面让大夫文种管理国政,另一方面,让范蠡训练军队,并采用了文种的美人计来诱惑吴王。等一切就绪后,他派范蠡带上越国最美的女子西施和郑量前往吴国,实施复兴越国的第一步骤,夫差果然中了勾践的美人计,对越国放松了警惕。经过十年的准备,越国举国攻打吴国,终于灭掉了吴国。
越王勾践灭吴后,并不甘心做一国之主,想成为东方的霸主,可是他担心原来帮助过他复国的范蠡等人起兵谋反,于是让文种接管了范蠡的兵权。范蠡早已料到越王会有这一手,因为他深知,越王只可以共患难而不能同享安乐。最后他决定走为上策,于是在风高月黑之夜,他乘着小船,涉三江,入五湖,最后来到了齐国。在齐国隐姓埋名,做起了陶瓷生意,最后成为一个大富商,人们又称他为陶朱公。
三国徐斡《中论修本》就运用了这个典故:"乘扁舟而济者,其身也要。"
说明:补充资料仅用于学习参考,请勿用于其它任何用途。
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