J. Deng, X. Song, and R. Shibasaki, “Dl-traff: Survey and benchmark of deep learning models for urban traffic prediction,” in Proceedings of the 30th ACM international conference on information & knowledge management, 2021, pp. 4515–4525. ...
[22] C. Song, Y. Lin, S. Guo, and H. Wan, “Spatial-temporal synchronous graph convolutional networks: A new framework for spatial-temporal network data forecasting,” in Proceedings of the AAAI Conference on Artificial Intelligence, 2020, pp. 914–921. [23] S. Guo, Y. Lin, N. Feng...
J. Deng, X. Song, and R. Shibasaki, “Dl-traff: Survey and benchmark of deep learning models for urban traffic prediction,” in Proceedings of the 30th ACM international conference on information & knowledge management, 2021, pp. 4515–4525. ...
来源会议 2024 International Conference on Artificial Intelligence and Power Systems (AIPS) 站内活动 0关于我们 百度学术集成海量学术资源,融合人工智能、深度学习、大数据分析等技术,为科研工作者提供全面快捷的学术服务。在这里我们保持学习的态度,不忘初心,砥砺前行。了解更多>>...
2024.[7] R. Jiang, Z. Wang, Y. Tao, C. Yang, X. Song, R. Shibasaki, S.-C. Chen, and M.-L. Shyu, “Learning social meta-knowledge for nowcasting human mobility in disaster,” in Proceedings of the ACM Web Conference 2023, 2023, pp. 2655–2665.[8] Y. Zhang, Y. Li, X....
[5] Y. Xia, Y. Liang, H. Wen, X. Liu, K. Wang, Z. Zhou, and R. Zimmermann, “Deciphering spatio-temporal graph forecasting: A causal lens and treatment,” in Thirty-seventh Conference on Neural Information Processing Systems, 2023. ...
[8] Y. Zhang, Y. Li, X. Zhou, X. Kong, and J. Luo, “Curb-gan: Conditional urban traffic estimation through spatio-temporal generative adversarial networks,” in Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2020, pp. 842–852. ...
基于MRSDAE-KPCA结合Bi-LST的滚动轴承剩余使用寿命预测.pdf,基于MRSDAE-KPCA 结合Bi-LST 的 滚动轴承剩余使用寿命预测 摘要:针对现有滚动轴承剩余使用寿命预测方法在提取数据特征时没有充分考虑数据的内部分布,且在构建健 康因子时还需要专家经验进行人工提取等问题,提
[5] Y. Xia, Y. Liang, H. Wen, X. Liu, K. Wang, Z. Zhou, and R. Zimmermann, “Deciphering spatio-temporal graph forecasting: A causal lens and treatment,” in Thirty-seventh Conference on Neural Information Processing Systems, 2023. ...
2024.[7] R. Jiang, Z. Wang, Y. Tao, C. Yang, X. Song, R. Shibasaki, S.-C. Chen, and M.-L. Shyu, “Learning social meta-knowledge for nowcasting human mobility in disaster,” in Proceedings of the ACM Web Conference 2023, 2023, pp. 2655–2665.[8] Y. Zhang, Y. Li, X....