Incremental Modeling Method Based on Support Vector Regression

Author

Wang Ling ; Mu Zhi-Cun ; Guo Hui

Author_Institution

Sch. of Inf. Eng., Univ. of Sci. & Technol., Beijing, China

fYear

2006

fDate

7-11 Aug. 2006

Firstpage

413

Lastpage

417

Abstract

A new incremental modeling method based on support vector regression proposed to improve the model accuracy and update the model for the increasing batch data in the real work. The proposed method has been applied to a practical case of modeling prediction ability of mechanical property of steel materials. Comparing with the traditional support vector machine incremental learning algorithm, the obtained model results demonstrate this promising method improves the model accuracy.

Keywords

batch processing (industrial); learning (artificial intelligence); regression analysis; steel industry; support vector machines; batch data; batch process; incremental learning; incremental modeling method; mechanical property; steel materials; support vector machine; support vector regression; Building materials; Data engineering; EMP radiation effects; Electronic mail; IEEE catalog; Machine learning; Mechanical factors; Predictive models; Steel; Support vector machines; batch processes; incremental learning; support vector regression;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2006. CCC 2006. Chinese

Conference_Location

Harbin

Print_ISBN

7-81077-802-1

Type

conf

DOI

10.1109/CHICC.2006.280585

Filename

4060548

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3216344