Selecting Hyper-Parameters of Gaussian Process Regression Based on Non-Inertial Particle Swarm Optimization in Internet of Things

Gaussian process regression (GPR) is frequently used for uncertain measurement and prediction of nonstationary time series in the Internet of Things data, nevertheless, the generalization and regression efficacy of GPR are directly impacted by its selection of hyper-parameters. In the study, a non-i...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Lanlan Kang, Ruey-Shun Chen, Naixue Xiong, Yeh-Cheng Chen, Yu-Xi Hu, Chien-Ming Chen
Format:	Article
Language:	English
Published:	IEEE 2019-01-01
Subjects:	Mutation Gaussian process regression time series regression hyper-parameters non-inertial particle swarm optimization
Online Access:	https://ieeexplore.ieee.org/document/8701439/