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October 11, 2025INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTOpen Access

Machine Learning Approaches for Predictive Maintenance in PV and Wind Energy Systems

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Authors

MKM. Santhosh KumarGITAM University

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Implication

Analysis highlights predictive maintenance using machine learning to improve reliability in photovoltaic and wind energy systems.

Key Points

  • Predictive maintenance enhances reliability and reduces downtime in renewable energy systems through machine learning.
  • Machine learning methodologies include supervised learning, unsupervised learning, and deep learning for system performance optimization.
  • Challenges in the study involve data quality and model precision, impacting the effectiveness of machine learning approaches.
  • This research emphasizes the importance of machine learning in advancing the operational efficiency of renewable energy technologies.

Cite This Study

M. Santhosh Kumar (2025) studied this question.

synapsesocial.com/papers/68e9b1b5ba7d64b6fc13206dhttps://doi.org/10.55041/ijsrem52939
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