Deep Time Series Intelligent Framework for Power Data Asset Evaluation
Power data asset evaluation occupies the core position in the digitization of the power industry. It involves the analysis and utilization of a large amount of power data. The key is to process time series data, such as power consumption and power generation. These data have both long-term and short...
Saved in:
| Main Authors: | Lihong Ge, Xin Li, Li Wang, Jian Wei, Bo Huang |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10988814/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Innovative SAR-optical data fusion for reflectance time series reconstruction in vegetation-covered regions
by: Shuaijun Liu, et al.
Published: (2025-06-01) -
Short-Term Water Demand Forecasting Using Machine Learning Approaches in a Case Study of a Water Distribution Network Located in Italy
by: Qidong Que, et al.
Published: (2024-09-01) -
Experimental Study on Long Short-term Memory Networks for Identifying P-wave Primary Phase
by: Tianzhe WANG, et al.
Published: (2025-03-01) -
Time Series Data Generation Method with High Reliability Based on ACGAN
by: Fang Liu, et al.
Published: (2025-01-01) -
Mitigating Long-Term Forecasting Bias in Time-Series Neural Networks via Ensemble of Short-Term Dependencies
by: Jiahui Wang, et al.
Published: (2025-06-01)