Algorithm of Sparse Least Squares Support Vector Machine

被引：0

作者：

Zhang, Yongli ^{[1
]}

Zhu, Yanwei ^{[2
]}

Lin, Shufei ^{[3
]}

Sun, Xiujuan ^{[2
]}

Zhang, Qiuna ^{[1
]}

Liu, Xiaohong ^{[1
]}

机构：

[1] He Bei Polytech Univ, Coll Light Ind, Dept Basic Courses, Tangshan, Peoples R China

[2] Tang Shan Teachers Coll Tang Shan, Dept Math & Informat Sci, Tang Shan, Peoples R China

[3] North Univ Ethn, Dept Comp, Yinchuan, Peoples R China

来源：

SMART MATERIALS AND INTELLIGENT SYSTEMS, PTS 1 AND 2 | 2011年 / 143-144卷

关键词：

Support Vector Machine; Least Squares Support Vector Machine; Greedy Algorithm; Wastewater Treatment;

D O I：

10.4028/www.scientific.net/AMR.143-144.1229

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Support Vector Machine has been widely studied in recent years. The algorithm of least squares support vector machine is studied, the shortcomings of the algorithm are given. The result of algorithm is lack of sparseness. In this paper greedy algorithm is introduced into the least squares support vector machine. Sparseness is obtained again. A new algorithm of sparse least squares support vector machine is given. The new algorithm was used to sewage treatment plant daily monitoring. Experimental results demonstrate the improved algorithm of support vector machine was successful.

引用

页码：1229 / +

页数：2