Open AccessAGA-GRU: An Optimized GRU Neural Network Model Based on Adaptive Genetic Algorithm
Author(s) -
Chenyao Bai
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1651/1/012146
Subject(s) - artificial neural network , gradient descent , computer science , generalization , genetic algorithm , algorithm , construct (python library) , artificial intelligence , machine learning , mathematics , mathematical analysis , programming language
The weight adjustment of gated recurrent unit (GRU) network depends on the gradient descent algorithm heavily, therefore this paper proposes an improved GRU neural network model based on adaptive genetic algorithm (AGA-GRU) to solve this problem. In this model, AGA is used to construct the optimization system, and the parameters of neural network model are optimized to improve the prediction performance. The results on UCI dataset show that the prediction accuracy of AGA-GRU model is significantly improved, and the generalization performance is stronger.