HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting
文献类型：期刊论文
| 作者 | Huang, Qihe3; Shen, Lei3; Zhang, Ruixin3; Cheng, Jiahuan3,4; Ding, Shouhong3; Zhou, Zhengyang2,5; Wang, Yang5 |
| 刊名 | THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 11
 |
| 出版日期 | 2024-10-01 |
| 卷号 | N/A页码:12608-12616 |
| 产权排序 | 4 |
| 文献子类 | Proceedings Paper |
| 英文摘要 | Multivariate time series (MTS) prediction has been widely adopted in various scenarios. Recently, some methods have employed patching to enhance local semantics and improve model performance. However, length-fixed patch are prone to losing temporal boundary information, such as complete peaks and periods. Moreover, existing methods mainly focus on modeling long-term dependencies across patches, while paying little attention to other dimensions (e.g., short-term dependencies within patches and complex interactions among cross-variavle patches). To address these challenges, we propose a pure MLP-based HDMixer, aiming to acquire patches with richer semantic information and efficiently modeling hierarchical interactions. Specifically, we design a Length-Extendable Patcher (LEP) tailored to MTS, which enriches the boundary information of patches and alleviates semantic incoherence in series. Subsequently, we devise a Hierarchical Dependency Explorer (HDE) based on pure MLPs. This explorer effectively models short-term dependencies within patches, long-term dependencies across patches, and complex interactions among variables. Extensive experiments on 9 real-world datasets demonstrate the superiority of our approach. The code is available at https://github.com/hqh0728/HDMixer. |
| WOS研究方向 | Computer Science |
| WOS记录号 | WOS:001241514400083 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/208023]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 通讯作者 | Zhou, Zhengyang |
| 作者单位 | 1.State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China 2.Tencent, Youtu Lab, Shanghai, Peoples R China 3.Johns Hopkins Univ, Baltimore, MD 21218 USA 4.USTC, Suzhou Inst Adv Res, Suzhou, Peoples R China 5.Univ Sci & Technol China USTC, Hefei, Peoples R China |
| 推荐引用方式 GB/T 7714 | Huang, Qihe,Shen, Lei,Zhang, Ruixin,et al. HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting[J]. THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 11,2024,N/A:12608-12616. |
| APA | Huang, Qihe.,Shen, Lei.,Zhang, Ruixin.,Cheng, Jiahuan.,Ding, Shouhong.,...&Wang, Yang.(2024).HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting.THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 11,N/A,12608-12616. |
| MLA | Huang, Qihe,et al."HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting".THIRTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, VOL 38 NO 11 N/A(2024):12608-12616. |
入库方式： OAI收割
来源：地理科学与资源研究所
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