FC-STGNN包括两个关键组件: •全连接图构建:过计算特征之间的点积,在所有时间戳之间建立传感器的全连接,从而能够全面地模拟多变量时间序列(MTS)数据中的时空(ST)依赖性,引入衰减矩阵以考虑传感器之间的时间距离,增强了FC图的精度,确保时间上接近的传感器展现出更强的相关性 •全连接图卷积:研究者提出了一种移动...
The code is available at https://github.com/Frank-Wang-oss/FCSTGNN. Dataset We use three datasets to evaluate our method, including C-MAPSS, UCI-HAR, and ISRUC-S3. C-MAPSS You can access here, and put the downloaded dataset into directory 'CMAPSSData'. For running the experiments on C...
The code is available at https://github.com/Frank-Wang-oss/FCSTGNN. Dataset We use three datasets to evaluate our method, including C-MAPSS, UCI-HAR, and ISRUC-S3. C-MAPSS You can access here, and put the downloaded dataset into directory 'CMAPSSData'. For running the experiments on C...
The code is available at https://github.com/Frank-Wang-oss/FCSTGNN. Dataset We use three datasets to evaluate our method, including C-MAPSS, UCI-HAR, and ISRUC-S3. C-MAPSS You can access here, and put the downloaded dataset into directory 'CMAPSSData'. For running the experiments on C...