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This research aims to improve the training efficiency of radial basis function (RBF) networks using evolutionary algorithms.

August 9, 2026MathematicsOpen Access

Introducing an Evolutionary Algorithm for the Optimal Training of RBF Networks

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Randomized trial demonstrates improved parameter optimization in machine learning models, suggesting a solution for training issues.

This research aims to improve the training efficiency of radial basis function (RBF) networks using evolutionary algorithms.
Developed a multi-stage evolutionary technique for training RBF networks.
Estimated parameter ranges using the K-Means algorithm.
Executed a genetic algorithm for parameter optimization.
Achieved effective parameter estimation for classification and regression tasks.
Demonstrated significant improvements in training outcomes over traditional methods.

Tsoulos et al. (2026) studied this question.

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