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Application of least squares support vector machine in futures price forecasting

机译:最小二乘支持向量机在期货价格预测中的应用

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Futures price forecasting based on least squares support vector machine is presented in the paper. In order to improve the prediction performance of least squares support vector machine, the experimental data can be normalized and appropriate parameters are selected by genetic algorithm. Least squares support vector machine is used to create the prediction model for futures price, and BP neural network is used to compare with least squares support vector machine. The experimental data of futures price are given. The prediction error of futures price by least squares support vector machine and BP neural network respectively are obtained. The analysis results show that futures price forecasting based on least squares support vector machine has excellent prediction results of futures price.
机译:提出了基于最小二乘支持向量机的期货价格预测方法。为了提高最小二乘支持向量机的预测性能,可以对实验数据进行归一化,并通过遗传算法选择合适的参数。最小二乘支持向量机用于创建期货价格预测模型,BP神经网络用于与最小二乘支持向量机进行比较。给出了期货价格的实验数据。利用最小二乘支持向量机和BP神经网络分别获得了期货价格的预测误差。分析结果表明,基于最小二乘支持向量机的期货价格预测具有优异的期货价格预测结果。

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