Publication Type : Conference Paper
Publisher : IEEE
Source : 2026 9th International Conference on Intelligent Computing and Control Systems (ICICCS)
Url : https://doi.org/10.1109/iciccs67901.2026.11502718
Campus : Bengaluru
School : School of Engineering
Department : Electrical and Electronics
Year : 2026
Abstract : Accurate prediction of solar irradiance is required for integrating solar energy into power grids and energy storage systems to improve efficiency and effectiveness. This paper represents a hybrid model which combines Grey Wolf Optimization (GWO) and Long Short Term Memory (LSTM). In order to increase prediction accuracy and lessen reliance on manual training, GWO is utilized to optimize the LSTM's parameters. The proposed model demonstrates improved accuracy when compared to traditional methods like normal LSTM.
Cite this Research Publication : Erol John DSilva, Syama S., V. S. Kirthika Devi, Solar Irradiance Prediction Using Grey Wolf Optimized LSTM (GWO-LSTM), 2026 9th International Conference on Intelligent Computing and Control Systems (ICICCS), IEEE, 2026, https://doi.org/10.1109/iciccs67901.2026.11502718