Dynamic Model of Liquid Copper Temperature Based on Weighted LS-SVM

被引：0

作者：

Li Yingdao ^{[1
]}

Ye Lingjian ^{[1
]}

Guan Hongwei ^{[1
]}

Zhong Weihong ^{[1
]}

Ma Xiushui ^{[1
]}

机构：

[1] Zhejiang Univ, Ningbo Inst Technol, Ningbo 315100, Zhejiang, Peoples R China

来源：

SIXTH INTERNATIONAL SYMPOSIUM ON PRECISION MECHANICAL MEASUREMENTS | 2013年 / 8916卷

关键词：

Scrap copper smelting; least squares; support vector machine; dynamic prediction method;

D O I：

10.1117/12.2035524

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Aimed to the difficult temperature measurement of scrap copper smelting process, this paper proposed a method of dynamic prediction method of furnace temperature based on weighted least squares support vector machine (WLS-SVM). In this method, the main input and output variables of the process squared error is given different weights to overcome the impact of the training sample anomalies, and use PSO for WLS-SVM parameters optimization, enhanced ability to adapt of dynamic model for the nonlinear time-varying characteristics, improved the prediction accuracy of the model. Finally, simulated through actual operating data of scrap copper smelting process, and verified the effectiveness of the method.

引用

页数：6

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