Predictive maintenance for aircraft cost reduction using machine learning
A hybrid predictive maintenance framework that combines Temporal Convolutional Networks for temporal feature extraction with Genetic Algorithms to select optimal features and Variational Autoencoders for detecting anomalies and Transformer-based models to classify failures and predict RUL is proposed.