Motivated by these problems, a hybrid learning algorithm combining genetic algorithm (GA) with gradient descent (GD), called HGAGD, is proposed in this paper.
In this paper, a hybrid gradient descent search algorithm (HGDSA) is proposed for training the parameters in fully-connected neural networks.
A Hybrid Genetic Algorithm + Gradient Descent Solution ... The success of this solution underscores the power of hybrid optimization techniques.
We have developed a new technology that allows for building a stable nonlinear predictive operator by using the combination of a neural network,
The first group employed GAs as a substitute for stochastic gradient descent (SGD) and backpropagation, focusing on parameter optimization
ABSTRACT. In this study, a modified hybrid optimization algorithm (HOA) is presented to address the limitations inherent in traditional
This research proposes a hybrid model that combines population-based heuristic algorithms with traditional gradient-based techniques to enhance
... hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The