A semantic-based, distance-proportional mutation for stock classification

作者：

Highlights：

• A semantic net that covers business fundamentals and market performance is created.

• A distance-proportional mutation operator guided by the semantic net is proposed.

• The impact that domain knowledge has on evolvability is established.

摘要

•A semantic net that covers business fundamentals and market performance is created.•A distance-proportional mutation operator guided by the semantic net is proposed.•The impact that domain knowledge has on evolvability is established.

论文关键词：Evolutionary computing,Domain knowledge,Semantic networks,Distance,Mutation

论文评审过程：Received 20 August 2017, Revised 28 October 2017, Accepted 12 November 2017, Available online 13 November 2017, Version of Record 14 December 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.11.029