Particle swarm optimization neural network and its application in soft-sensing modeling

Authors:
Guochu Chen;Jinshou Yu
Affiliations:
Research Institute of Automation, East China University of Science and Technology, Shanghai, China;Research Institute of Automation, East China University of Science and Technology, Shanghai, China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Year:
2005

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Abstract

Particle swarm optimization algorithm (PSO) is applied to train artificial neural network (NN) to construct a neural network based on particle swarm optimization algorithm (PSONN). Then, PSONN is employed to construct a practical soft-sensor of gasoline endpoint of main fractionator of fluid catalytic cracking unit (FCCU). The obtained results indicate that soft-sensing model based on PSONN has better performance than soft-sensing model based on BPNN and the new method proposed by this paper is feasible and effective in soft-sensing modeling of gasoline endpoint.