This paper proposes a solution to this problem for Radial Basis Function (RBF) networks and General Regression Neural Network (GRNN) which is a kind of radial ...
Abstract. The topology of a neural network has a significant importance on the network's performance. Although this is well known, finding optimal.
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This paper describes an approach for pattern recognition using genetic algorithm and general regression neural network (GRNN). The designed system can be ...
Nov 16, 2019 · Abstract—The aim of this project is to develop a code to discover the optimal σ value that maximum the F1 score and.
This paper proposes a solution to this problem for Radial Basis Function (RBF) networks and General Regression Neural Network (GRNN) which is a kind of radial ...
Nov 16, 2019 · Four algorithms which can be used to solve this problem are: Genetic Regression Neural ... optimization methods, such. as gradient descent ...
In the present study, genetic algorithms are proposed to automatically configure RBF networks. The network configuration is formed as a subset selection problem ...
The aim of this project is to develop a code to discover the optimal sigma value that maximum the F1 score and the optimal rho value that maximizes the ...
The radial basis function (RBF) network is an efficient function approximator. Theoretical researches focus on the capabilities of the network to reach an ...
Jul 10, 2023 · This paper present a Mixed Radial Basis Function Neural Network (MRBFNN) training using Genetic Algorithm (GA). The choice of the type of Radial ...