Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks-Reference-Cited by-同舟云学术

Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

Published:2018-06-27 Issue: Volume: Page:
ISSN:
Container-title:The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval
language:
Short-container-title:

Author:

Lai Guokun¹,Chang Wei-Cheng¹,Yang Yiming¹,Liu Hanxiao¹

Affiliation:

1. Carnegie Mellon University, Pittsburgh, PA, USA

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3209978.3210006

Reference36 articles.

1. G. E. Box G. M. Jenkins G. C. Reinsel and G. M. Ljung . Time series analysis: forecasting and control . John Wiley & Sons 2015 . G. E. Box G. M. Jenkins G. C. Reinsel and G. M. Ljung. Time series analysis: forecasting and control. John Wiley & Sons 2015.

2. Support vector machine with adaptive parameters in financial time series forecasting

Cited by 1149 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. TFformer: A time–frequency domain bidirectional sequence-level attention based transformer for interpretable long-term sequence forecasting;Pattern Recognition;2025-02

2. Exploring spatio-temporal dynamics for enhanced wind turbine condition monitoring;Mechanical Systems and Signal Processing;2025-01

3. MGSFformer: A Multi-Granularity Spatiotemporal Fusion Transformer for air quality prediction;Information Fusion;2025-01

4. A decomposition-ensemble-integration framework for carbon price forecasting;Expert Systems with Applications;2024-12

5. Multi-attention network with redundant information filtering for multi-horizon forecasting in multivariate time series;Expert Systems with Applications;2024-12