Multi-Layer Perceptron Training by Genetic Algorithms

Luka Gajić; Dušan Cvetnić; Timea Bezdan; Nebojša Bačanin Džakula

doi:10.15308/sinteza-2020-301-306

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Multi-Layer Perceptron Training by Genetic Algorithms

Luka Gajić Dušan Cvetnić Timea Bezdan Nebojša Bačanin Džakula

Year: 2020 Pages: 301-306

DOI: 10.15308/sinteza-2020-301-306

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Abstract

In this paper, the authors are presenting one of the ways to train Artificial Neural Networks (ANN) using a predefined set of weights as biases as input parameters, generated by the Genetic Algorithm (GA)

Keywords:

Computer science Genetic algorithm Artificial neural network Perceptron Training (meteorology) Artificial intelligence Set (abstract data type) Layer (electronics) Algorithm Training set Machine learning Pattern recognition (psychology)

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Neural Networks and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Fuzzy Logic and Control Systems

Physical Sciences → Computer Science → Artificial Intelligence

Metaheuristic Optimization Algorithms Research

Physical Sciences → Computer Science → Artificial Intelligence

Multi-Layer Perceptron Training by Genetic Algorithms

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