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Intelligent Engineering Systems through Artificial Neural Networks, Volume 16

Editor
Cihan H. Dagli
Cihan H. Dagli
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Anna L. Buczak
Anna L. Buczak
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David L. Enke
David L. Enke
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Mark Embrechts
Mark Embrechts
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Okan Ersoy
Okan Ersoy
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ISBN-10:
0791802566
No. of Pages:
1000
Publisher:
ASME Press
Publication date:
2006

The focus of this paper is to predict a binary time series using recurrent networks. We evaluate the performance of linear classifier and neural networks such as Elman and Time Delay Neural Networks for predicting binary time series. The performance of these networks is evaluated with respect to factors such as neural network architecture (number of hidden layers and neurons, learning rates, training functions used) and lag window sizes. Both the networks performed better as compared to linear classifier and performance of Elman neural network was best among the neural networks.

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