Abstract
A hybrid parallel neural network that combined a forward neural network with a recurrent neural network was proposed to predict the biomass concentration in fermentation. Each of forward neural network and recurrent neural network worked as an individual channel of the hybrid neural network and made up each other. Their accumulated error was reduced by another neural network. The maximum error of hybrid neural network was proved be less than or equal to that of the channel and finally the steps of algorithm were given. The simulation shows the proposed approach is effective in the complex environment.
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© 2012 Springer-Verlag Berlin Heidelberg
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Zhang, D., Cheng, B., Wu, A. (2012). Prediction of Biomass Concentration with Hybrid Neural Network. In: Wang, J., Yen, G.G., Polycarpou, M.M. (eds) Advances in Neural Networks – ISNN 2012. ISNN 2012. Lecture Notes in Computer Science, vol 7368. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31362-2_70
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DOI: https://doi.org/10.1007/978-3-642-31362-2_70
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31361-5
Online ISBN: 978-3-642-31362-2
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