Particle Swarm Optimization Neural Network and Its Application in Soft-Sensing Modeling

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.