Optimizing photovoltaic output performance prediction: a deep learning approach with LSTM neural networks and Adam optimizer / Syasya Nadhirah Hamedon, Juliana Johari and Fazlina Ahmat Ruslan

This study introduces an innovative approach to optimizing photovoltaic (PV) output performance prediction through Deep Learning, specifically employing Long Short-Term Memory (LSTM) networks and the Adaptive Moment Estimation (Adam) optimizer. The research is carried out using MATLAB R2023a, and th...

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Bibliographic Details
Main Authors: Hamedon, Syasya Nadhirah, Johari, Juliana, Ahmat Ruslan, Fazlina
Format: Article
Language:English
Published: UiTM Press 2024
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/105786/1/105786.pdf
https://ir.uitm.edu.my/id/eprint/105786/
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