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This document presents a hybrid deep learning framework, ELSTMD, for multivariate renewable energy forecasting, addressing the challenges posed by the intermittent nature of renewable sources. The model enhances predictive accuracy through feature orthogonalization, dimensionality reduction, and temporal sequence learning, and is validated across datasets from Turkey and India. Experimental results demonstrate that ELSTMD outperforms 21 traditional and modern forecasting models, confirming its robustness an

Author

ghosharkoprabho

Language

EN