In order to improve the accuracy of Internet of Things data mining,the study proposes an Internet of Things data mining method based on swarm intelligence algorithm,which improves the particle swarm optimization algorithm;introduces adaptive inertia weight factor;and combines K-means clustering algorithm to further optimize the location of clustering center,so that the algorithm is not easy to fall into local optimal.In this way,the convergence and accuracy of the algorithm is improved.Simulation results show that this algorithm can effectively improve the accuracy of data mining in the Internet of Things.
关键词
数据挖掘/物联网/粒子群算法/K-means聚类算法
Key words
Data mining/Internet of Things/Particle swarm optimization/K-means clustering algorithm
维普
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