A method for generating switching operation sequences based on generative adversarial networks

Xiaopeng Chen; Chenjing Wu; Suxiong Cai; Xianfeng Lu; Binbin Zhang

doi:10.1117/12.3049701

18 October 2024 A method for generating switching operation sequences based on generative adversarial networks

Xiaopeng Chen, Chenjing Wu, Suxiong Cai, Xianfeng Lu, Binbin Zhang

Author Affiliations +

Proceedings Volume 13277, Sixth International Conference on Wireless Communications and Smart Grid (ICWCSG 2024); 132770T (2024) https://doi.org/10.1117/12.3049701
Event: 2024 6th International Conference on Wireless Communications and Smart Grid, 2024, Sipsongpanna, China

Abstract

To address the issues of low efficiency and accuracy in the generation of switching operation tickets, a method for generating switching operation sequences based on Generative Adversarial Networks (GAN) is proposed. Firstly, the SDAR (Sequence Decomposition And Reconstruction) module is used to perform multi-scale decomposition and reconstruction of the original operation task sequences, capturing both the overall and local features of the operation task sequences. Secondly, an A-LSTM (Attention-Long Short Term Memory) network is introduced to enhance the accuracy of the generated switching operation sequences. Finally, the generator of the proposed model is constructed based on the SDAR module and the A-LSTM network. Experimental results show that the proposed model achieves a 47.10% improvement in RMSE and a 4.26% improvement in R² compared to LSTM, and a 27.33% improvement in RMSE and a 1.73% improvement in R² compared to WGAN.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xiaopeng Chen, Chenjing Wu, Suxiong Cai, Xianfeng Lu, and Binbin Zhang "A method for generating switching operation sequences based on generative adversarial networks", Proc. SPIE 13277, Sixth International Conference on Wireless Communications and Smart Grid (ICWCSG 2024), 132770T (18 October 2024); https://doi.org/10.1117/12.3049701

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