In this paper, a hybrid neural network/genetic algorithm technique is presented, aiming at designing a feature extractor that leads to highly separable classes in the feature space. The application ...

Aiming to the problem of too many input and output parameters of the BP neural network, a multiple population genetic algorithm (MPGA) is introduced to optimize the internal weights and thresholds of ...

deforce (DErivative Free Optimization foR Cascade forward nEural networks) is a Python library that implements variants and the traditional version of Cascade Forward Neural Networks. These include ...

We propose a hybrid quantum-classical neural network architecture where each neuron is a variational quantum circuit. We empirically analyze the performance of this hybrid neural network on a series ...

A surrogate model for these objectives is presented, and a genetic algorithm with and without acceleration using that surrogate model are compared. The following sections include overviews of both the ...

Taking the experimental data from the pool test, the back-propagation neural network with genetic algorithm (GA-BPNN) forecasting model was established. Besides, the other prediction methods were ...

About This package provides the Python "pyneurgen" module, which contains several classes for implementing grammatical evolution, a form of genetic programming, and classes for neural networks. These ...