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A Lifetime Extended Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles via Self-Learning Fuzzy Reinforcement Learning
In the paper, a fuzzy reinforcement learning-based energy management strategy for fuel cell hybrid electric vehicles is proposed to reduce fuel consumption, maintain the batteries' long-term operation, and extend the lifetime of the fuel cells system.
Data-driven prognostics based on time-frequency analysis and symbolic recurrent neural network for fuel cells under dynamic load
Data-centric prognostics is beneficial to improve the reliability and safety of proton exchange membrane fuel cell (PEMFC).
Learning from Pseudo Lesion: A Self-supervised Framework for COVID-19 Diagnosis
The pairs of normal and pseudo COVID-19 images were then used to train an encoder-decoder architecture based U-Net for image restoration, which does not require any labelled data.
A Quality-Diversity Controllable GAN for Text Generation
Text generation is a critical and difficult natural language processing task.
Slim Embedding Layers for Recurrent Neural Language Models
When the vocabulary size is large, the space taken to store the model parameters becomes the bottleneck for the use of recurrent neural language models.
Une m\'ethode discriminant formation simple pour la traduction automatique avec Grands Caract\'eristiques
Marge infus{\'e} algorithmes d{\'e}tendus (MIRAS) dominent mod{\`e}le de tuning dans la traduction automatique statistique dans le cas des grandes caract{\'e}ristiques de l{'}{\'e}chelle, mais ils sont {\'e}galement c{\'e}l{\`e}bres pour la complexit{\'e} de mise en {\oe}uvre.
