1) least square support vect
最小二乘支撑向量机
1.
Based on the Lyapunov stability theory,this dissertation is mainly on the design of the robust adaptive controllers for uncertain time delay systems subject to different assumptions by using linear matrix inequalities(LMIs),and the design of the adaptive control of a class of nonlinear discrete-time systems by the use of least square support vector machine algorithm (LSSVM).
本文主要基于Lyapunov稳定性理论,以线性矩阵不等式(LMI)和最小二乘支撑向量机(LSSVM)为主要工具,研究了不确定时滞系统满足不同设计要求的各种鲁棒自适应控制问题和一类仿射非线性离散系统的自适应控制问题。
3) fuzzy least squares support vector machine
最小二乘模糊支撑向量机
1.
Research of fuzzy least squares support vector machines;
最小二乘模糊支撑向量机研究
4) 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
5) 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
6) 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
补充资料：非线性最小二乘拟合
分子式：
CAS号：
性质：用最小二乘法拟合非线性方程。有些变量之间的非线性模型，通过变量变换可以化为线性模型，此称为外在线性。而有些变量之间的非线性模型，通过变量变换不能化为线性模型，通称为内在非线性。对于非线性模型y=f(ξ,θ)+ε，其残差平方和。S(θ)是θ的函数，当模型关于θ是非线性的，正规方程关于θ也是非线性的。基于使残差平方和s(θ)达到极小的原理求出θ的估计值，拟合非线性回归方程。
CAS号：
性质：用最小二乘法拟合非线性方程。有些变量之间的非线性模型，通过变量变换可以化为线性模型，此称为外在线性。而有些变量之间的非线性模型，通过变量变换不能化为线性模型，通称为内在非线性。对于非线性模型y=f(ξ,θ)+ε，其残差平方和。S(θ)是θ的函数，当模型关于θ是非线性的，正规方程关于θ也是非线性的。基于使残差平方和s(θ)达到极小的原理求出θ的估计值，拟合非线性回归方程。
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