A novel hybrid photovoltaic current prediction model utilizing singular spectrum analysis, adaptive beluga whale optimization, and improved extreme learning machine
Key Points
The prediction model utilizes singular spectrum analysis and extreme learning machine techniques to enhance accuracy.
Key performance metrics show significant improvements in current prediction compared to traditional models.
This analysis incorporates hybrid methods, leveraging both adaptive optimization and machine learning principles.
Results highlight a practical approach for improving energy forecasting, which can optimize photovoltaic system management.