Stacked Heterogeneous Neural Networks for Time Series Forecasting
A hybrid model for time series forecasting is proposed. It is a stacked neural network, containing one normal multilayer perceptron with bipolar sigmoid activation functions, and the other with an exponential activation function in the output layer. As shown by the case studies, the proposed stacked...
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| Format: | Article |
| Language: | English |
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Hindawi Limited
2010-01-01
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| Series: | Mathematical Problems in Engineering |
| Online Access: | http://dx.doi.org/10.1155/2010/373648 |
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doaj-027215dbe5e5432f9a8f11596d1cdf5a2020-11-25T01:05:37ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472010-01-01201010.1155/2010/373648373648Stacked Heterogeneous Neural Networks for Time Series ForecastingFlorin Leon0Mihai Horia Zaharia1Faculty of Automatic Control and Computer Engineering, Technical University “Gheorghe Asachi” of Iaşi, Boulevard Mangeron 53A, 700050 Iaşi, RomaniaFaculty of Automatic Control and Computer Engineering, Technical University “Gheorghe Asachi” of Iaşi, Boulevard Mangeron 53A, 700050 Iaşi, RomaniaA hybrid model for time series forecasting is proposed. It is a stacked neural network, containing one normal multilayer perceptron with bipolar sigmoid activation functions, and the other with an exponential activation function in the output layer. As shown by the case studies, the proposed stacked hybrid neural model performs well on a variety of benchmark time series. The combination of weights of the two stack components that leads to optimal performance is also studied.http://dx.doi.org/10.1155/2010/373648 |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Florin Leon Mihai Horia Zaharia |
| spellingShingle |
Florin Leon Mihai Horia Zaharia Stacked Heterogeneous Neural Networks for Time Series Forecasting Mathematical Problems in Engineering |
| author_facet |
Florin Leon Mihai Horia Zaharia |
| author_sort |
Florin Leon |
| title |
Stacked Heterogeneous Neural Networks for Time Series Forecasting |
| title_short |
Stacked Heterogeneous Neural Networks for Time Series Forecasting |
| title_full |
Stacked Heterogeneous Neural Networks for Time Series Forecasting |
| title_fullStr |
Stacked Heterogeneous Neural Networks for Time Series Forecasting |
| title_full_unstemmed |
Stacked Heterogeneous Neural Networks for Time Series Forecasting |
| title_sort |
stacked heterogeneous neural networks for time series forecasting |
| publisher |
Hindawi Limited |
| series |
Mathematical Problems in Engineering |
| issn |
1024-123X 1563-5147 |
| publishDate |
2010-01-01 |
| description |
A hybrid model for time series forecasting is proposed. It is a stacked neural network, containing one normal multilayer perceptron with bipolar sigmoid activation functions, and the other with an exponential activation function in the output layer. As shown by the case studies, the proposed stacked hybrid neural model performs well on a variety of benchmark time series. The combination of weights of the two stack components that leads to optimal performance is also studied. |
| url |
http://dx.doi.org/10.1155/2010/373648 |
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AT florinleon stackedheterogeneousneuralnetworksfortimeseriesforecasting AT mihaihoriazaharia stackedheterogeneousneuralnetworksfortimeseriesforecasting |
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