Simulation of Intelligent Internet of Things System Based on Machine Learning and Clustering Algorithm

Authors

  • Liang Guo School of Computer Science and Information Engineering, Anyang Institute of Technology, Anyang, Henan, 455000, China

Abstract

With the evolution of cloud computing technology, researchers are constantly examining ways to use network technology to simulate intelligent system operations, increase the number of practical application functions, and assist with the design of cloud computing platforms. The latter requires a sound understanding of computer science and engineering, to which research scholars have contributed several theories. The development of cloud computing network platforms has given users access to a great number of resources, which in turn has seen an increase in the number of users who use cloud computing network platforms for data processing. However, in the long term, the current structure of cloud computing network platforms will not be able to provide the quality that users expect from a network platform. In this paper, the particle swarm algorithm is analysed and its current shortcomings are addressed in order to improve its performance. The bad particles and parameters in the particle swarm are adjusted so that the algorithm can better meet the construction requirements of a cloud computing platform.

Keywords: machine learning; clustering algorithm; intelligent Internet of Things (IoT); system simulation

Cite As

L. Guo, "Simulation of Intelligent Internet of Things System Based on Machine Learning and Clustering
Algorithm", Engineering Intelligent Systems, vol. 29 no. 6, pp. 375-378, 2021.










 

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Published

2021-11-01

Issue

Vol. 29 No. 6 (2021): International Journal of Engineering Intelligent Systems

Section

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