Use of artificial neural networks in chemical addiction stages detection of adolescents

Abstract

Today there is no unified approach to description of the stages of addiction and evolution of adolescent addiction formation. In this paper we consider two main points. At first we describe the different approaches to the selection stages of addictive behavior. The second point is the description of using the method of constructing artificial neural networks to determine the formation of chemical addiction. Also this article describes the theoretical approaches to the evolution stages of dependence and to the construction of artificial neural networks. It is experimentally proved the importance and logic of constructing assessment stage of addictive behavior, described the main parameters of this assessment, and considered the main characteristics of sentence groups. Thus, we demonstrate the number of objective advantages of artificial neural networks to the classical methods. It is create possibility using artificial neural networks in professionals’ practice working with the assessment of adolescent addiction.