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14 February 2024 Improved particle swarm optimization least squares support vector machine method for train wireless time delay prediction
Huigang Xu, Liyan Zhang, Changxian Li
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Proceedings Volume 13018, International Conference on Smart Transportation and City Engineering (STCE 2023); 130184S (2024) https://doi.org/10.1117/12.3024713
Event: International Conference on Smart Transportation and City Engineering (STCE 2023), 2023, Chongqing, China
Abstract
In the process of high-speed movement of multiple unit trains, the train wireless communication delay has a very important impact on driving safety. If the delay is too long, the train will not be able to control, traction and brake normally. Therefore, a wireless delay prediction model based on Singular Spectrum Analysis (SSA)-Quantum Particle Swarm Optimization (QPSO) to optimize Least Squares Support Vector Machine (LSSVM) is proposed. Firstly, to lower the complexity of the sequence, the measured time series is broken down into components corresponding to different eigenvalues after singular value processing. During the decomposition process, the window length is selected using the Cao method. Secondly, each sub sequence is trained by QPSO-LSSVM model to determine the optimal parameters of LSSVM. Finally, each predicted subsequence is superimposed to get the final predicted results. The simulation results show that the proposed method has higher prediction accuracy and minimum prediction error compared to SSA-PSOLSSVM, EMD-QPSO-LSSVM, and QPSO-LSSSVM methods.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Huigang Xu, Liyan Zhang, and Changxian Li "Improved particle swarm optimization least squares support vector machine method for train wireless time delay prediction", Proc. SPIE 13018, International Conference on Smart Transportation and City Engineering (STCE 2023), 130184S (14 February 2024); https://doi.org/10.1117/12.3024713
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KEYWORDS
Education and training
Particle swarm optimization
Windows
Quantum processing
Mathematical optimization
Matrices
Singular value decomposition
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