Anomaly Detection for Wind Turbines Using Long Short-Term Memory-Based Variational Autoencoder Wasserstein Generation Adversarial Network under Semi-Supervised Training
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- Sergen Tumse & Mehmet Bilgili & Alper Yildirim & Besir Sahin, 2024. "Comparative Analysis of Global Onshore and Offshore Wind Energy Characteristics and Potentials," Sustainability, MDPI, vol. 16(15), pages 1-28, August.
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Keywords
wind turbine; anomaly detection; long short-term memory-based (LSTM-based); variational autoencoder Wasserstein generation adversarial network (VAE-WGAN); semi-supervised training;All these keywords.
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