Recognizing human activity in mobile crowdsensing environment using optimized k-NN algorithm

作者：

Highlights：

• In this paper, a novel model is proposed for recognizing human activities.

• k-NN classifier was employed in our model for classifying human activities.

• Particle Swarm Optimization algorithm was used for optimizing k-NN classifier.

• The results of our model demonstrated promising results.

摘要

•In this paper, a novel model is proposed for recognizing human activities.•k-NN classifier was employed in our model for classifying human activities.•Particle Swarm Optimization algorithm was used for optimizing k-NN classifier.•The results of our model demonstrated promising results.

论文关键词：Mobile crowd sensing,Human activities,Particle swarm optimization (PSO),Optimization algorithms,k-Nearest Neighbor (k-NN),Classification,Parameter optimization,Swarm intelligent

论文评审过程：Received 26 December 2017, Revised 1 April 2018, Accepted 11 April 2018, Available online 12 April 2018, Version of Record 22 April 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.04.017