Список литературы

2518-1092

Research result. Information technologies

2518-1092

10.18413/2518-1092-2023-8-4-0-5

3301

ARTIFICIAL INTELLIGENCE AND DECISION MAKING

<strong>DESIGN OF RECURRENT NEURAL NETWORKS FOR CLASSIFICATION OF AGE DIFFERENCES IN THE FUNCTIONING OF THE SYMBOLIC SYSTEM OF QUANTITY ASSESSMENT</strong>

Malykh

Sergey Borisovich

Malykh

Sergey Borisovich

malykhsb@mail.ru

Asadullaev

Rustam Gennadievich

Asadullaev

Rustam Gennadievich

asadullaev@bsu.edu.ru

Sitnikova

Maria Aleksandrovna

Sitnikova

Maria Aleksandrovna

sitnikovamary46@gmail.com

2023

8400

The article presents the result of the development and training of 4 recurrent neural network architectures to solve the problem of classifying age-related differences in the functioning of the symbolic system of quantity assessment. When designing neural networks, some effective algorithms were used: cells with long short-term memory, a modification that allows a signal to be fed to the neural network in forward and reverse order, and preliminary 1D convolutions of the signal before feeding it to recurrent layers. The best result on all data sets was demonstrated by a recurrent neural network with signal pre-convolution layers. Accuracy varies between 86-88% depending on the dataset. The specified accuracy was obtained on data to which the baseline correction algorithm was applied.

recurrent neural networkslong short-term memorymachine learninganalysis of multidimensional datadeep learningfunctional near-infrared spectroscopy

The study was supported by the Russian National Science Foundation grant No. 22-28-02030 "Neurocognitive mechanisms of symbolic numerical skills".

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