The upper and lower envelopes are constructed by using LSSVM regression instead of spline interpolation in EMD.
同时以LSSVM回归方式形成包络线，以取代传统EMD中的三次样条插值；
A fault diagnosis method for satellite attitude control systems is presented based on least squares support vector machine (LSSVM).
提出了一种基于最小二乘支持向量机(LSSVM)非线性观测器的卫星姿态控制系统故障诊断方法。
After studying on modeling theories of SVM and the parameter optimization of SVM, the Least Squares Support Vector Machines tool LSSVM.
在研究支持向量机的建模理论和参数优化方法的基础上，将最小二乘法支持向量机工具LSSVM。
A slope stability evaluation method based on particle swarm optimization (PSO) and least square support vector machine (LSSVM) is proposed.
提出了基于粒子群算法(PSO)和最小二乘支持向量机(LSSVM)的边坡稳定性评价方法。
The features of two methods, i. e. least square support vector machine (LSSVM) and generalized regression neural network (GRNN) are compared and analyzed.
比较分析了最小二乘支持向量机（LSSVM）和广义回归神经网络（GRNN）这两种方法的特点。
Structure identification depends on the potential of data in time window. parameter identification is based on LSSVM with fast speed and high precision of identification.
以时间窗内数据的势能作为结构辨识依据，同时采用最小二乘支持向量机辨识系统参数，辨识速度快、精度高。
The experiments on several pattern classification problems show that HS-LSSVM has high sparseness while holds good classification performance and its sparse process is fast.
支持向量回归机是一种解决回归问题的重要方法，其预测速度与支持向量的稀疏性成正比。
In the paper online identification based on time window and least square support vector machine (LSSVM) for T-S model is proposed, including structure and parameter identification.
本文提出了基于时间窗的最小二乘支持向量机t - S模型在线辨识算法，包括结构辨识和参数辨识。
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.
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。
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.
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。
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