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STGPT2UGAN: Spatio-Temporal GPT-2 United Generative Adversarial Network for Wind Speed Prediction in Turbine Network
1. Introduction Since entering the 21st century, the issue of energy consumption has garnered widespread attention throughout the world [1]. To solve this issue, renewable energy (e.g., wind energy) comes to prominence. Currently, more and more countries are beginning to vigorously establish wind farms. The core of a wind farm is the turbine network, which consists of multiple turbines. Each turbine is treated as a node in the network.
Green Computation Offloading With DRL in Multi‐Access Edge Computing
Conflicts of Interest The authors declare no conflicts of interest. References 1, , , , and , “FL-Incentivizer: FL-NFT and FL-Tokens for Federated Learning Model Trading and Training,” IEEE Access 11 (2023): 4381–4399. 2, , , et al., “Deep Learning for Air Pollutant Concentration Prediction: A Review,” Atmospheric Environment 290 (2022): 119347. 3, , , et al., “Federated Learning Based on CTC for Heterogeneous Internet of Things,” IEEE Internet of Things Journal 10, no. 24 (2023): 22673–22685.
A Novel Symmetric Fine-Coarse Neural Network for 3D Human Action Recognition Based on Point Cloud Sequences
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