A comparative analysis of LSTM, SVM, and GSTANN models for enhancing solar power prediction
Solar power prediction is crucial for integrating renewable energy into the grid, but current methods often struggle with accuracy due to the limitations of machine learning algorithms. This study aims to enhance prediction accuracy by comparing the performance of Long Short-Term Memory (LSTM)...
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Main Authors: | M. Helmy, Muhammad Fareezy Fahmy, Yusoff, Siti Hajar, Mansor, Hasmah, Gunawan, Teddy Surya, Chowdhury, Israth Jahan, Mohd Sapihie, Siti Nadiah |
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Format: | Proceeding Paper |
Language: | English |
Published: |
IEEE
2024
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Subjects: | |
Online Access: | http://irep.iium.edu.my/115179/13/115179_%20A%20comparative%20analysis%20of%20LSTM.pdf http://irep.iium.edu.my/115179/ https://ieeexplore.ieee.org/document/10675536 https://doi.org/10.1109/ICSIMA62563.2024.10675536 |
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