Establishing Gaussian Process Fault Prediction Model Based on Improved PSO

LYU Jiapeng; SHI Xianjun; WANG Kang

doi:10.3969/j.issn.1671-637x.2020.11.015

Journals >Electronics Optics & Control >Volume 27 >Issue 11 >Page 75 > Article

Electronics Optics & Control
Vol. 27, Issue 11, 75 (2020)

Establishing Gaussian Process Fault Prediction Model Based on Improved PSO

LYU Jiapeng, SHI Xianjun, and WANG Kang

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[in Chinese]

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DOI: 10.3969/j.issn.1671-637x.2020.11.015 Cite this Article

LYU Jiapeng, SHI Xianjun, WANG Kang. Establishing Gaussian Process Fault Prediction Model Based on Improved PSO[J]. Electronics Optics & Control, 2020, 27(11): 75 Copy Citation Text

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References

[5] RASMUSSEN C E,WILLIAMS C K I.Gaussian processes for machine learning［M］.Cambridge:The MIT Press, 2006.

[6] POLYAK B T.The conjugate gradient method in extreme problems［J］.USSR Computational Mathematics and Mathematical Physics,1969,9(4):94-112.

[9] CHEN Y G,LI L X,XIAO J H,et al.Particle swarm optimizer with crossover operation［J］.Engineering Applications of Artificial Intelligence,2018,70:159-169.

[10] JORDEHI A R.Enhanced leader particle swarm optimisation(ELPSO):an efficient algorithm for parameter estimation of photovoltaic (PV) cells and modules［J］.Solar Energy,2018,159:78-87.

[11] THARWAT A,ELHOSENY M,HASSANIEN A E,et al.Intelligent Bézier curve-based path planning model using chaotic particle swarm optimization algorithm［J］.Cluster Computing,2019,22(2):4745-4766.

LYU Jiapeng, SHI Xianjun, WANG Kang. Establishing Gaussian Process Fault Prediction Model Based on Improved PSO[J]. Electronics Optics & Control, 2020, 27(11): 75

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