最小二乘支持向量机(Least Square SVM，LS-SVM)是标准SVM的一种新扩展，它用等式约束代替标准SVM的不等式约束，将二次规划问题转化为线性方程组求解...
基于40个网页-相关网页
In this paper, soft sensor modeling method based on Least Square SVM (LS SVM) is proposed, and cross validation method is used to select hyper-parameter of LS SVM model.
本文研究了基于最小二乘支持向量机的软测量建模方法，并用交叉验证的方法进行支持向量机参数选择。
In this method, subtractive clustering was adopted to divide the input space into several sub-spaces, and sub-models were built by Least Square SVM (ls SVM) in every sub-space.
该建模方法通过减聚类方法将输入空间划分为一些小的局部空间，在每个局部空间中用最小二乘支持向量机(LS - SVM)建立子模型。
A novel prediction model for remaining capacity of batteries based on least square support vector machine (LS-SVM) was proposed.
提出了一种最小二乘支持向量机的电池剩余电量预测新模型。
应用推荐