首页    期刊浏览 2024年09月12日 星期四
登录注册

文章基本信息

  • 标题:Identification and Prediction Using Neuro-Fuzzy Networks with Symbiotic Adaptive Particle Swarm Optimization
  • 本地全文:下载
  • 作者:C.-J. Lin ; C.-C. Peng ; C.-Y. Lee
  • 期刊名称:Informatica
  • 印刷版ISSN:1514-8327
  • 电子版ISSN:1854-3871
  • 出版年度:2011
  • 卷号:35
  • 期号:1
  • 出版社:The Slovene Society Informatika, Ljubljana
  • 摘要:This study presents a novel symbiotic adaptive particle swarm optimization (SAPSO) for neuro-fuzzy network design. The proposed SAPSO uses symbiotic evolution and adaptive particle swarm optimization with neighborhood operator (APSO-NO) to improve the performance of the traditional PSO. In APSO-NO, we combine the neighborhood operator and the adaptive particle swarm optimization to tune the particles that are most significant. Simulation results have shown that the proposed SAPSO performs better and requires less computation time than the traditional PSO.
  • 关键词:particle swarm optimization; symbiotic evolution; neuro-fuzzy network; identification; prediction
国家哲学社会科学文献中心版权所有