An online learning algorithm with adaptive forgetting factors for feedforward neural networks in financial time series forecasting
An online learning algorithm with adaptive forgetting factors for feedforward neural networks in financial time series forecasting
复制标题
金融时间序列预测中前馈神经网络的自适应遗忘因子在线学习算法
DOI：
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发表时间：
2007
影响因子：
--
通讯作者：
Kin Keung Lai
中科院分区：
文献类型：
--
作者：
Shouyang Wang;Lean Yu;Kin Keung Lai
In this study, an online learning algorithm for feedforward neural networks (FNN) based on the optimized learning rate and adaptive forgetting factor is proposed for online financial time series prediction. The new learning algorithm is developed for online predictions in terms of the gradient descent technique, and can speed up the FNN learning process substantially relative to the standard FNN algorithm, with simultaneous preservation of stability of the learning process. In order to verify the effectiveness and efficiency of the proposed online learning algorithm, two typical financial time series are chosen as testing targets for illustration purposes.
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DOI：
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发表时间：
1994-04
期刊：
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影响因子：
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作者：
G. Deboeck
通讯作者：
G. Deboeck
影响因子：
5.4
作者：
IIGUNI, Y;SAKAI, H;TOKUMARU, H
通讯作者：
TOKUMARU, H
影响因子：
5.3
作者：
AbuMostafa, YS;Atiya, AF
通讯作者：
Atiya, AF
影响因子：
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作者：
Dong-Chul Park;M. El-Sharkawi;R. Marks
通讯作者：
Dong-Chul Park;M. El-Sharkawi;R. Marks
DOI：
10.1016/s0045-7906(00)00063-x
发表时间：
2002-11
期刊：
Comput. Electr. Eng.
影响因子：
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作者：
D. Sha;V. Bajic
通讯作者：
D. Sha;V. Bajic