A novel gray wolf optimizer with RNA crossover operation for tackling the non-parametric modeling problem of FCC process

作者：

Highlights：

• A novel GWO with RNA encoding crossover-operation is proposed.

• The adaptive control parameter is designed to enhance the performance.

• Experimental results comparison between RNA-GWO and the other algorithms are performed.

• The RNA-GWO optimized WNN is used for modeling the FCC process.

摘要

•A novel GWO with RNA encoding crossover-operation is proposed.•The adaptive control parameter is designed to enhance the performance.•Experimental results comparison between RNA-GWO and the other algorithms are performed.•The RNA-GWO optimized WNN is used for modeling the FCC process.

论文关键词：Gray wolf optimizer,RNA computing,Fluid catalytic cracking (FCC) process,Wavelet neural network,Modeling

论文评审过程：Received 14 September 2020, Revised 21 December 2020, Accepted 4 January 2021, Available online 11 January 2021, Version of Record 25 January 2021.

论文官网地址：https://doi.org/10.1016/j.knosys.2021.106751