{
  "id": 13190,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1881404",
  "title": "Hybrid fuzzy C-means and deep learning framework for intelligent fault classification in solar PV systems",
  "summary": "Photovoltaic (PV) systems have proven themselves to be a viable alternative energy source; however, there are multiple faults related to PV systems which cause energy losses and low efficiencies. Manual or rule-based algorithms are traditionally used for fault diagnosis, which are not efficient and unsuitable for real-time applications. In this paper, a novel hybrid intelligent classification system for PV fault detection is proposed by integrating Fuzzy C-Means (FCM) clustering and Deep Learnin",
  "authors": "V. Vignesh",
  "category": "research",
  "topics": "healthcare,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-23T00:00:00.000Z",
  "fetched_at": "2026-07-25T05:10:48.796Z",
  "source_slug": "x-frontiers-in-artificial-intelligence",
  "source_name": "Frontiers in Artificial Intelligence",
  "source_homepage": "https://www.frontiersin.org/journals/artificial-intelligence",
  "ethics_ai_record_url": "https://ethics.ai/record/13190",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1881404",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}