Variable Chromosome Genetic Algorithm for Structure Learning in Neural Networks to Imitate Human Brain

Variable Chromosome Genetic Algorithm for Structure Learning in Neural Networks to Imitate Human Brain

This paper proposes the variable chromosome genetic algorithm (VCGA) for structure learning in neural networks. Currently, the structural parameters of neural networks, i.e., number of neurons, coupling relations, number of layers, etc., have mostly been designed on the basis of heuristic knowledge...

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Bibliographic Details
Main Authors: Kang-moon Park, Donghoon Shin, Sung-do Chi
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Applied Sciences
Subjects:
variable chromosome genetic algorithm
deep learning
structure learning
artificial neural network
neural architecture search
Online Access:https://www.mdpi.com/2076-3417/9/15/3176

Internet

https://www.mdpi.com/2076-3417/9/15/3176

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