计算机工程与应用2012，Vol.48Issue(26)：36-38,59,4.DOI:10.3778/j.issn.1002-8331.2012.26.008
基于群算法的过程参量聚类研究
Clustering research of process parameters based on particle swarm optimization
摘要
Abstract
The paper adopts the Particle Swarm Optimization(PSO) to solve the parameters clustering problem of complex processes. The basic mechanism of PSO is presented in the paper. The clustering simulation on temperatures and rotation speeds of the calcination process verifies the practicability of PSO in parameters clustering of similar complex processes. The clustering features and parameters setting of PSO are discussed in detail. Combined with artificial immune, some improved methods are brought forward to achieve better performances.关键词
聚类分析/粒子群优化/群算法/人工免疫Key words
clustering analysis/ Particle Swarm Optimization (PSO)/ swarm algorithm/ artificial immune分类
信息技术与安全科学引用本文复制引用
朱燕飞,胡夏云,唐雄民..基于群算法的过程参量聚类研究[J].计算机工程与应用,2012,48(26):36-38,59,4.基金项目
广东工业大学合生珠江创新项目(No.HSZJ2011015). （No.HSZJ2011015）
