Chengqing Yu
Orcid: 0000-0001-8314-8251
According to our database1,
Chengqing Yu
authored at least 17 papers
between 2020 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis.
IEEE Trans. Knowl. Data Eng., January, 2025
MGSFformer: A Multi-Granularity Spatiotemporal Fusion Transformer for air quality prediction.
Inf. Fusion, 2025
2024
MRIformer: A multi-resolution interactive transformer for wind speed multi-step prediction.
Inf. Sci., 2024
Semi-supervised anomaly detection with contamination-resilience and incremental training.
Eng. Appl. Artif. Intell., 2024
Eng. Appl. Artif. Intell., 2024
LightWeather: Harnessing Absolute Positional Encoding to Efficient and Scalable Global Weather Forecasting.
CoRR, 2024
GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024
Proceedings of the International Joint Conference on Neural Networks, 2024
2023
Attention mechanism is useful in spatio-temporal wind speed prediction: Evidence from China.
Appl. Soft Comput., November, 2023
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysis.
CoRR, 2023
DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
Clustering-property Matters: A Cluster-aware Network for Large Scale Multivariate Time Series Forecasting.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023
2022
A new crude oil futures forecasting method based on fusing quadratic forecasting with residual forecasting.
Digit. Signal Process., 2022
A new ensemble deep graph reinforcement learning network for spatio-temporal traffic volume forecasting in a freeway network.
Digit. Signal Process., 2022
A dynamic ensemble deep deterministic policy gradient recursive network for spatiotemporal traffic speed forecasting in an urban road network.
Digit. Signal Process., 2022
A data-driven hybrid ensemble AI model for COVID-19 infection forecast using multiple neural networks and reinforced learning.
Comput. Biol. Medicine, 2022
2020
A novel axle temperature forecasting method based on decomposition, reinforcement learning optimization and neural network.
Adv. Eng. Informatics, 2020