(Edwards et al., 2019; Bruce et al., 2024) to train deep neural network models to play these games. In this work, videos from … train deep neural network models to play Sokoban. These models were further improved with reinforcement learning in …

(Edwards et al., 2019; Bruce et al., 2024) to train deep neural network models to play these games. In this work, videos from … train deep neural network models to play Sokoban. These models were further improved with reinforcement learning in …

) is applied to aggregate experts' fuzzy estimates based on the assigned authority levels. Subsequently, a deep neural … network (DNN) is constructed to defuzzify the aggregation result. We then apply the auto-weighting deep-learning fuzzy …

This study proposes a feedforward deep neural network to predict the parameters of the lithium-ion battery in electric …, mileage, voltage, velocity, and state-of-charge. The proposed inverse model is superior to the feedforward deep neural network … virtual functions into a deep neural network model's inverse model can improve the accuracy of battery and electric vehicle …