文献类型：会议论文

英文题名：Particle swarm optimization neural network and its application in soft-sensing modeling

作者：Chen, GC; Yu, JS

机构：[1]E China Univ Sci & Technol, Res Inst Automat, Shanghai 200237, Peoples R China

会议论文集：1st International Conference on Natural Computation (ICNC 2005)

会议日期：AUG 27-29, 2005

会议地点：Changsha, PEOPLES R CHINA

语种：英文

摘要：Particle swarm optimization algorithm (PSO) is applied to train artificial neural network (NN) to construct a neural network based on particle swarm optimitization 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.