Minimal learning parameters-based adaptive neural control for vehicle active suspensions with input saturation
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DOI: 10.1016/j.neucom.2018.07.096
Abstract: Abstract In this paper, a neural network (NN) control method is developed for nonlinear quarter vehicle active suspension systems (VASSs) which have the features of parameter uncertainties, input saturation and road disturbance, whose aim is… read more here.
Keywords: vehicle active; input saturation; control; minimal learning ... See more keywords
Meta-Learning With Task-Adaptive Selection
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DOI: 10.1109/tcsvt.2025.3557706
Abstract: The gradient-based meta-learning algorithm gains meta-learning parameters from a pool of tasks. Starting from the obtained meta-learning parameters, it can achieve better results through fast fine-tuning with only a few gradient descent updates. The two-layer… read more here.
Keywords: meta; learning parameters; selection; meta learning ... See more keywords
Learning the Parameters of ELECTRE-Based Primal-Dual Sorting Methods that Use Either Characteristic or Limiting Profiles
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DOI: 10.3390/axioms12030294
Abstract: Two multicriteria-sorting methods that generalize the relational paradigm have been recently presented in the literature. One uses objects representative of classes, the other uses objects in the limiting boundaries of classes; both can use either… read more here.
Keywords: use either; methodology; learning parameters; sorting methods ... See more keywords