Abstract
A two-layer hierarchical neural network is proposed to predict the product qualities of an industrial KTI GK-V ethylene pyrolysis process. The first layer of the model is used to classify these changes into different operating conditions. In the second layer, the process under each operating condition is modeled using bootstrap aggregated neural networks (BANN) with sequential training algorithm. The overall output is obtained by combining all the trained networks. Results of application to the actual process show that the proposed soft-sensing model possesses good generalization capability.
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Zhou, Q., Xu, Y.M.: Predict the Product Yields Profile of Ethylene Pyrolysis Furnace by Multi-Models. In: Proceedings of the IFAC International Conference on Intelligent Control and Signal Processing, Faro, Portugal, April 8-11 (2003)
Sjoberg, J., Zhang, Q., Ljung, L., Benveniste, A., et al.: Nonlinear Black-box Modeling in System Identification: a Unified Overview. Automatica 31, 1691–1724 (1995)
Bhat, N., McAvoy, T.: Use of Neural Nets for Dynamic Modeling and Control of Chemical Process Systems. Comput. Chem. Eng. 14, 573–583 (1990)
Sridhar, D.V., Seagrave, R.C., Bartlett, E.B.: Process Modeling Using Stacked Neural Networks. AICHE Journal 42, 2529–2539 (1996)
Xiong, Z.H., Zhang, J.: Optimal Control of Fed-Batch Processes Based on Multiple Neural Networks. Applied Intelligence 22, 149–161 (2005)
Zhang, J.: Sequential Training of Bootstrap Aggregated Neural Networks for Nonlinear System Modeling. In: Proceedings of the American Control Conference, Anchorage, Alaska, U.S.A, pp. 531–536 (2002)
Jordan, M.I., Jacobs, R.A.: Hierarchical Mixture of Experts and the EM Algorithm. Neural Computation 6, 181–214 (1994)
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© 2006 Springer-Verlag Berlin Heidelberg
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Zhou, Q., Xiong, Z., Zhang, J., Xu, Y. (2006). Hierarchical Neural Network Based Product Quality Prediction of Industrial Ethylene Pyrolysis Process. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_165
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DOI: https://doi.org/10.1007/11760191_165
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
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