Xu, Mengfan and Pan, Junyang (2024) Short-term Electricity Load Forecasting Based on Improved Seagull Algorithm Optimized Gated Recurrent Unit Neural Network. EAI Endorsed Transactions on Energy Web.
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Abstract
INTRODUCTION: The complexity of the power network, changes in weather conditions, diverse geographical locations, and holiday activities comprehensively affect the normal operation of power loads. Power load changes have characteristics such as non stationarity, randomness, seasonality, and high vol
| Item Type: | Article |
|---|---|
| Date Deposited: | 04 Mar 2026 18:12 |
| Last Modified: | 11 Apr 2026 00:26 |
| URI: | http://eprints.eai.eu/id/eprint/51563 |
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