Colleges Employment Forecasting by Least Squares Support Vector Machine

Author

Jing, Lv ; Yanqing, Zhang

Author_Institution

Harbin Univ. of Sci. & Technol., Harbin, China

Volume

2

fYear

2012

fDate

23-25 March 2012

Firstpage

169

Lastpage

172

Abstract

Colleges employment forecasting based on least squares support vector machine is proposed in the paper. Least squares support vector machine is an improved support vector machine, which can use equality constraints for the error instead of inequality constraints. Colleges employment rate of Xinjiang agricultural university from 1997 to 2006 is used to show the effectiveness of least squares support vector machine.The comparison results of forecasting error for colleges employment rate between least squares support vector machine and BP neural network indicate that least squares support vector machine has a higher forecasting accuracy than BP neural network.

Keywords

backpropagation; educational administrative data processing; educational institutions; forecasting theory; least squares approximations; neural nets; regression analysis; support vector machines; BP neural network; Xinjiang agricultural university; colleges employment forecasting; equality constraints; least squares support vector machine; regression function; Accuracy; Artificial neural networks; Educational institutions; Employment; Forecasting; Support vector machines; Training; colleges employment; forecasting technology; least squares support vector machine; practical application; regression function;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science and Electronics Engineering (ICCSEE), 2012 International Conference on

Conference_Location

Hangzhou

Print_ISBN

978-1-4673-0689-8

Type

conf

DOI

10.1109/ICCSEE.2012.455

Filename

6187927