KALFormer:使

Xing Dong1, Qianwei Yang2, Wenbo Cheng3

  • 1School of Basic Medical Sciences, Guizhou University of Traditional Chinese Medicine, Guiyang, China.

PloS one
|January 6, 2026
PubMed
概括

KALFormer是一个新的框架,通过整合知识和注意力机制来改进长期时间序列预测. 这种方法提高了复杂数据模式的准确性和可靠性.

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