电子学报2012，Vol.40Issue(9)：1885-1888,4.DOI:10.3969/j.issn.0372-2112.2012.09.029
交叉前置式粒子群优化算法及其在催化裂化C3含量软测量中的应用
Particle Swarm Optimization with Pre-Crossover and Its Application in Soft-Sensor of C3 Concentration of FCCU
摘要
Abstract
An improved particle swaim optimization with pre-crossover(PSOPC) was proposed to avoid the premature convergence of particle swarm optimization algorithm. An auxiliary population was introduced in which the particles with low fitness but high diversity after each generation were stored.The pre-crossover between the particle in the swarm and the individual in the extra population was implemented, which helps increase the diversity of the particle swarm so as to improve the global convergence. PSOPC was used to train BP neural network to construct a soft-sensing model of C3 concentration of the fluid catalytic cracker unit (FCCU). The experimental results show that the model based on PSOPC and neural network has good precision and strong generalization.关键词
粒子群优化算法/优化/催化裂化/C3含量Key words
particle swarm optimization optimization/ fluid catalytic cracker unit/O3 concentration分类
信息技术与安全科学引用本文复制引用
商雨青,许伟,顾幸生..交叉前置式粒子群优化算法及其在催化裂化C3含量软测量中的应用[J].电子学报,2012,40(9):1885-1888,4.基金项目
国家863高技术研究发展计划(No.2009AA04Z141) （No.2009AA04Z141）
上海市基础研究重点项目(No.10JC1405800) （No.10JC1405800）
上海市教委重点学科(J51901) （J51901）
