Colleges employment forecasting by least squares support vector machine

摘要

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.