PREDICTION OF COMPUTER GAME ADDICTION IN CHILDREN USING DEVELOPED ARTIFICIAL NEURAL NETWORKS (ANN) AND MULTIPLE LINEAR REGRESSION (MLR) MODELS

Autor:	Esma UZUNHİSARLIKCI, Erhan KAVUNCUOĞLU, Hanife AKGÜL
Jazyk:	German<br />English<br />Turkish
Rok vydání:	2021
Předmět:	artificial neural network multiple linear regression prediction of computer game addiction expert system. History of scholarship and learning. The humanities AZ20-999 Social sciences (General) H1-99
Zdroj:	Trakya Üniversitesi Sosyal Bilimler Dergisi, Vol 23, Iss 2, Pp 551-570 (2021)
Druh dokumentu:	article
ISSN:	1305-7766 2587-2451
DOI:	10.26468/trakyasobed.789767
Popis:	Game addiction in children plays a major role in the mental and physical development of the child. Therefore, various scales are used to examine computer game addiction of children and various input parameters (age, gender, daily play time, etc.) are utilized in scales. The purpose of this study is to project a system that estimates whether the child is addicted to the game when looking at the input parameters. Artificial Neural Networks (ANN) and Multiple Linear Regression (MLR) techniques were used to design this system. In order to measure the predictive performance of the developed models, the Root Mean Squared Error (RMSE), and Correlation Coefficient (R) criteria were examined respectively and it was observed that the model developed by ANN predicted CGA with high accuracy.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/d7c7d4cbd85d463b91b0cffa24ca5144 Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF