支持向量回归算法在高校招生预测中的应用

E. Ying
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引用次数: 4

摘要

本文将支持向量回归算法应用于高校招生预测。由于高校招生预测是一个非线性回归问题,在支持向量回归模型中,将高校招生的输入训练数据非线性映射到高维空间中。以2000 - 2008年四川省高校招生规模为样本,验证支持向量回归方法的有效性。然后给出了支持向量回归方法与BP神经网络的预测曲线,并比较了支持向量回归方法与BP神经网络对高校招生人数的预测误差。比较支持向量回归方法与BP神经网络对高校招生人数的预测误差,结果表明支持向量回归方法比BP神经网络具有更高的预测精度。
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Application of Support Vector Regression Algorithm in Colleges Recruiting Students Prediction
Support vector regression algorithm is applied to colleges recruiting students prediction in the paper. As colleges recruiting students prediction is a nonlinear regression problem, the input training data of colleges recruiting students are nonlinearly mapped into a high dimensional space in support vector regression model. The amount of colleges recruiting students of Sichuan province from 2000 to 2008 is used to prove the effectiveness of support vector regression method. Then,the forecasting curves of support vector regression method and BP neural network and the comparison of forecasting error for amount of colleges recruiting students between support vector regression method and BP neural network are given in this study.The comparison results of forecasting error for amount of colleges recruiting students between support vector regression method and BP neural network indicate that support vector regression method has a higher forecasting accuracy than BP neural network.
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