Application-specific clustering in wireless sensor networks using combined fuzzy firefly algorithm and random forest

作者：

Highlights：

• Introducing combined fuzzy firefly algorithm and random forest (named FFA-RF).

• Collecting a dataset by utilizing FFA for offline clustering in different applications.

• Performing RF to learn the behavioral pattern of FFA in proper cluster-head selection.

• Applying the trained FFA-RF model for online clustering in new unseen WSNs.

摘要

•Introducing combined fuzzy firefly algorithm and random forest (named FFA-RF).•Collecting a dataset by utilizing FFA for offline clustering in different applications.•Performing RF to learn the behavioral pattern of FFA in proper cluster-head selection.•Applying the trained FFA-RF model for online clustering in new unseen WSNs.

论文关键词：Wireless sensor networks,Application-specific clustering,Machine learning,Fuzzy inference system,Firefly algorithm,Random forest

论文评审过程：Received 12 June 2021, Revised 21 July 2022, Accepted 1 August 2022, Available online 5 August 2022, Version of Record 17 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118365