Oct 22, 2024 · We propose an evolutionary algorithm for optimizing the hidden layer size of three-layer perceptrons. The optimization problem is posed in terms ...
Multilayer perceptron training using an evolutionary algorithm
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Feb 26, 2009 · This paper takes a step in that direction by introducing an EA for Multi-Layer Perceptron (MLP) learning, called Perceptron Learning using ...
Multiple Layer Perceptron networks trained with backpropagation algorithm are very frequently used to solve a wide variety of real-world problems. Usually a ...
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May 13, 2022 · In this paper, we propose an alternative learning-based method for DMOPs, a deep multi-layer perceptron-based predictor to generate an initial population for ...
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In this paper we deal with variants of genetic learning applied for the structure optimization and weights evolution of multi-layer perceptron networks. Several ...
In this work, multilayer perceptron (MLP) has been trained by differential evolution algorithm (DEA) and the performance of the neural network has been ...
The architecture of MLP. Genetic algorithm (GA) and particle swarm optimization (PSO), as evolutionary algorithms, have been employed to train the neural ...
This paper takes a step in that direction by introducing an EA for Multi-Layer Perceptron (MLP) learning, called Perceptron Learning using Genetic algorithm ( ...
In this research, we introduce and validate an evolutionary optimization framework to train multilayer perceptrons, which are simple feedforward neural networks ...
In this research, we introduce and validate an evolutionary optimization framework to train multilayer perceptrons, which are simple feedforward neural networks ...