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Hierarchical Neural Network Based Product Quality Prediction of Industrial Ethylene Pyrolysis Process

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Part of the book series:Lecture Notes in Computer Science ((LNTCS,volume 3973))

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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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Author information

Authors and Affiliations

  1. Department of Automation, Tsinghua University, Beijng, 100084, P.R. China

    Qiang Zhou, Zhihua Xiong & Yongmao Xu

  2. School of Chemical Engineering and Advanced Materials, University of Newcastle, Newcastle upon Tyne, NE1 7RU, UK

    Jie Zhang

Authors
  1. Qiang Zhou

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  2. Zhihua Xiong

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  3. Jie Zhang

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  4. Yongmao Xu

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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd, 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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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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