基于智能支持向量机回归模型的金融数据预测

Prediction of Finance Data Based Intelligent Support Vector Regression

摘要: 针对金融数据的非线性、时变性、随机性、模糊性、不确定性等特点，提出一种崭新的智能支持向量回归模型，并且运用一种新型的遗传算法优选模型参数。实验结果表明，所提出的智能支持向量回归模型预测金融数据比BP神经网络模型预测精度高、速度快。

Abstract: Aiming at nonlinear, time variant, random, fuzziness and uncertainty of finance data, we propose a new intelligent support vector regression model and use new genetic algorithm to optimize the model’s parameters. Experiment results show that intelligent support vector regression has higher accuracy and runs faster than BP Neural Networks.