Particle Swarm Optimization Fuzzy Neural Network and its Application in Soft-Sensor Modeling of Acrylonitrile Yield

Firstly, particle swarm optimization fuzzy neural network (PSOFNN) is proposed and the algorithm flow of PSOFNN are given in this paper. Secondly, PSOFNN is applied in soft-sensor modeling of acrylonitrile yield. The new method assumes that fuzzy neural network (FNN) is used to construct the soft-sensor model of acrylonitrile yield and particle swarm optimization algorithm (PSO) is employed to optimize parameters of FNN. Moreover, how to choose the auxiliary variables of soft-sensor is studied carefully. Experiment results show that the model based on PSOFNN has higher precision and better performance than the model based on PSONN. The method proposed by this paper is feasible and effective in soft-sensor of acrylonitrile yield.