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Stacked Heterogeneous Neural Networks for Time Series Forecasting
Joint Authors
Zaharia, Mihai Horia
Leon, Florin
Source
Mathematical Problems in Engineering
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-20, 20 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-05-03
Country of Publication
Egypt
No. of Pages
20
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Leon, Florin& Zaharia, Mihai Horia. 2010. Stacked Heterogeneous Neural Networks for Time Series Forecasting. Mathematical Problems in Engineering،Vol. 2010, no. 2010, pp.1-20.
https://search.emarefa.net/detail/BIM-466943
Modern Language Association (MLA)
Leon, Florin& Zaharia, Mihai Horia. Stacked Heterogeneous Neural Networks for Time Series Forecasting. Mathematical Problems in Engineering No. 2010 (2010), pp.1-20.
https://search.emarefa.net/detail/BIM-466943
American Medical Association (AMA)
Leon, Florin& Zaharia, Mihai Horia. Stacked Heterogeneous Neural Networks for Time Series Forecasting. Mathematical Problems in Engineering. 2010. Vol. 2010, no. 2010, pp.1-20.
https://search.emarefa.net/detail/BIM-466943
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-466943