RETRACTED: Research on smart grid management and security guarantee of sports stadiums based on GCNN-GRU and self-attention mechanism - Li, Song (Frontiers in Energy Research, 2023)
Smart grid management and security in sports stadiums have become global concerns and important topics in the field of deep learning. To address the challenges, this paper proposes a method based on graph convolutional neural network (GCNN) with gated recurrent units (GRU) and self-attention mechanism. The goal is to predict trends and influencing factors in smart grid management and security of sports stadiums, facilitating the formulation of optimization strategies and policies. Firstly, historical data of sports stadium grid management and security undergo preprocessing using GCNN and GRU networks to extract time series information.Then, the GCNN network is utilized to analyze smart grid data of sports stadiums. Finally, the GCNN-GRU model captures spatial correlations and temporal dynamics, while the self-attention mechanism enhances focus on relevant information. The experimental results indicate that the proposed method based on GCNN-GRU and self-attention mechanism effectively addresses the challenges of smart grid management and security in sports stadiums. It accurately predicts trends and influencing factors in smart grid management and security, facilitating the formulation of optimization strategies and policies. These results also demonstrate that our method has achieved outstanding performance in the image generation task and exhibits strong adaptability across different datasets.