Hierarchical neural network based product quality prediction of industrial ethylene pyrolysis process

Zhou, Q; Xiong, Z; Zhang, J; Xu, Y

doi:10.1007/11760191_165

Hierarchical neural network based product quality prediction of industrial ethylene pyrolysis process

Lookup NU author(s): Qiusha Zhou, Dr Zhihua Xiong, Dr Jie Zhang ORCiD

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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. © Springer-Verlag Berlin Heidelberg 2006.