| 利用VLRBP神经网络改善汇率预测 |
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| 引用本文： | 王向宇,须文波,孙俊,赵琪.利用VLRBP神经网络改善汇率预测[J].计算机工程与应用,2010,46(6):208-213. |
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| 作者姓名： | 王向宇 须文波 孙俊 赵琪 |
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| 作者单位： | 江南大学,信息工程学院,江苏,无锡,214122 |
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| 基金项目： | 国家自然科学基金(No.60474030)~~ |
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| 摘 要： | 分别使用基于滑动窗口的VLRBP神经网络模型和基于C-C相空间重构的VLRBP神经网络模型及ARIMA-GARCH模型对欧元汇率时间序列建模和预测，通过比较发现基于C-C相空间重构的VLRBP神经网络对于含有大量非线性成分的欧元汇率时间序列的预测比较准确。同时，为了提高基于滑动窗口的VLRBP网络的泛化性能，提出在训练VLRBP神经网络时应用浴盆曲线方法选取隐层神经元个数和滑动窗口尺寸。
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| 关 键 词： | 时间序列 VLRBP神经网络 相空间重构 ARIMA-GARCH模型 浴盆曲线 |
| 收稿时间： | 2009-2-12 |
| 修稿时间： | 2009-5-7
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Improving foreign exchange rates forecast by using VLRBP artificial neural networks |
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| WANG Xiang-yu,XU Wen-bo,SUN Jun,ZHAO Qi.Improving foreign exchange rates forecast by using VLRBP artificial neural networks[J].Computer Engineering and Applications,2010,46(6):208-213. |
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| Authors: | WANG Xiang-yu XU Wen-bo SUN Jun ZHAO Qi |
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| Affiliation: | WANG Xiang-yu,XU Wen-bo,SUN Jun,ZHAO Qi School of Information Technology,Jiangnan University,Wuxi,Jiangsu 214122,China |
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| Abstract: | It builds a sliding window neural networks model,a neural networks model which is based on phase space reconstruc- tion and an ARIMA-GARCH model,and then the euro foreign exchange rate is forecasted by using the three models.The result shows that the VLRBP neural networks which is based on C-C phase space reconstruction produces better porformance than the other methods in forecasting the euro foreign exchange rate which has a great amount nonlinear components.To improve the gen- eralization performance of ... |
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| Keywords: | time aeries Variable Learning Rate Back Propagation(VLRBP) neural networks phase space reconstruction ARIMAGARCH model bathtub curve |
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