使用Transformer网络进行负荷预测

根据提供的引用内容，可以使用Transformer网络进行负荷预测任务。Transformer模型是一种使用注意力机制的模型，在负荷预测任务中具有很好的性能。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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- *1* *3* [[时间序列预测]基于BP、LSTM、CNN-LSTM神经网络算法的单特征用电负荷预测[保姆级手把手教学]](https://blog.csdn.net/didiaopao/article/details/127039659)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
- *2* [PyTorch搭建Transformer实现多变量多步长时间序列预测（负荷预测）](https://blog.csdn.net/Cyril_KI/article/details/125479940)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v92^chatsearchT3_1"}}] [.reference_item style="max-width: 50%"]
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