Possibilities of artificial intellect in detection of predisposition to drug addiction

Автор: Yasnitskiy Leonid N., Gratsilev Vadim I., Kulyashova Julia S., Cherepanov Fyodor M.

Журнал: Вестник Пермского университета. Философия. Психология. Социология @fsf-vestnik

Рубрика: Психология

Статья в выпуске: 1 (21), 2015 года.

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A computer program is designed to determine the degree of predisposition of a human to drug addiction. The program is based on the neural network trained on the results of sociological surveys. Error of neural network model is less than 1 %. With the help of neural network a model evaluates the importance of factors that can influence predisposition to drug addiction. The most important factors are: the level of education, having friends who use drugs, temperament type, number of children in the family, financial situation. Neural network model allows to evaluate the effect of varying the parameters characterizing the man and his predisposition to addiction and select the optimal combination of these parameters for each individual and thus to receive individual recommendations for reducing drug addiction.

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Drug addiction, addiction, recommendations, artificial intelligence, neural network, regularities, mathematical modeling, prediction

Короткий адрес: https://sciup.org/147203025

IDR: 147203025

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