A new methodology for identifying unreliable sensors in data fusion

作者：

Highlights：

• A new proposal for identifying unreliable sensors without the knowledge of the ground truth is presented.

• The new proposal is based on the theory of S-Model Learning Automata.

• This novel model allows to handle an arbitrary number of sensors and achieves a faster convergence.

摘要

•A new proposal for identifying unreliable sensors without the knowledge of the ground truth is presented.•The new proposal is based on the theory of S-Model Learning Automata.•This novel model allows to handle an arbitrary number of sensors and achieves a faster convergence.

论文关键词：Unreliable sensors identification,Learning automata,S-Model environment

论文评审过程：Received 17 May 2017, Revised 1 August 2017, Accepted 2 September 2017, Available online 6 September 2017, Version of Record 4 October 2017.

论文官网地址：https://doi.org/10.1016/j.knosys.2017.09.001