Random ensemble of fuzzy rule-based models

作者：

Highlights：

• We design bagging and boosting mechanisms of assembling fuzzy rule-based models.

• We quantify and analyze the performance of the ensemble mechanism.

• We thoroughly study the predominant parameters of resulting ensemble models.

摘要

•We design bagging and boosting mechanisms of assembling fuzzy rule-based models.•We quantify and analyze the performance of the ensemble mechanism.•We thoroughly study the predominant parameters of resulting ensemble models.

论文关键词：Random ensemble,Fuzzy rule-based model,Random forest,Boosting,Performance

论文评审过程：Received 26 July 2018, Revised 8 May 2019, Accepted 8 May 2019, Available online 16 May 2019, Version of Record 16 August 2019.

论文官网地址：https://doi.org/10.1016/j.knosys.2019.05.011