Particle swarm optimization based extreme learning neuro-fuzzy system for regression and classification

作者：

Highlights：

• Improves regularized fuzzy-neuro system using optimization.

• Regularization parameter is tuned by particle swarm optimization.

• Shows that proposed technique gives the best generalization performance.

摘要

•Improves regularized fuzzy-neuro system using optimization.•Regularization parameter is tuned by particle swarm optimization.•Shows that proposed technique gives the best generalization performance.

论文关键词：Takagi–Sugeno–Kang (TSK) fuzzy inference system,ELM based neuro-fuzzy system,Regularization,Regression and multi-class classification

论文评审过程：Received 15 March 2017, Revised 13 September 2017, Accepted 14 September 2017, Available online 28 September 2017, Version of Record 6 October 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.09.037