Dynamic Salp swarm algorithm for feature selection

作者：

Highlights：

• A dynamic Salp swarm algorithm is proposed for feature selection.

• The development of novel update equation to improve solutions diversity.

• The development of new Local search algorithm to improve algorithm exploitation.

• The algorithm was tested on 23 datasets and it is outperformed other algorithms.

摘要

•A dynamic Salp swarm algorithm is proposed for feature selection.•The development of novel update equation to improve solutions diversity.•The development of new Local search algorithm to improve algorithm exploitation.•The algorithm was tested on 23 datasets and it is outperformed other algorithms.

论文关键词：Salp swarm algorithm,Feature selection,Singer chaotic map,Local search algorithm (LSA)

论文评审过程：Received 8 November 2019, Revised 30 June 2020, Accepted 8 August 2020, Available online 10 August 2020, Version of Record 23 September 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113873