Prediction of Floor Water Bursting Based on Combining Principal Component Analysis and Support Vector Machine

被引：0

作者：

Liu, Beizhan ^{[1
]}

Bing, Liang ^{[2
]}

机构：

[1] Liaoning Tech Univ, Coll Sci, Fuxin 123000, Liaoning, Peoples R China

[2] Liaoning Tech Univ, Sch Mech & Engn, Fuxin 123000, Liaoning, Peoples R China

来源：

FUZZY INFORMATION AND ENGINEERING 2010, VOL 1 | 2010年 / 78卷

关键词：

Principal component analysis; support vector machine; floor water bursting; prediction;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

A prediction method that based on combing principal component analysis and support vector machine is proposed. Principal component analysis was used to select input variable. The prediction model considers all-sided influencing factors and avoids the low precision and slow training induced by over-input. The example shows that it eliminates the relevance among factors, reduces the input variables and improves the accuracy and efficiency.

引用

页码：591 / +

页数：2