Investigation of the influence of aggressive behavior of minors on their deviant activities based on the Buss-Durkee method by constructing a fuzzy logic production system

The problem of deviant behavior prevention in minors is particularly relevant at present since this age group belongs to the most socially vulnerable category. In order to identify the deviation in adolescents, it is necessary to analyze and identify manifestations of their aggressive behavior. This study is based on the identification of predisposition to the development of aggressive behavior based on the Buss-Durkee method. 10 factors identified by the authors of this technique have been considered. A five-level classifier for input and output factors of a fuzzy logic production system is proposed. The membership functions are selected by applying the method of expert assessments reflecting the competent opinion of a specialist regarding the affiliation of the elements with the term set. Fuzzy logic rules have been defined, in the capacity of which the data on the test results obtained by minors aged 14-15 years have been entered and supplemented with a view to ensuring the completeness of the system. To reduce the number of fuzzy logic rules and enable consistency in it, a hierarchical structure of input factors has been formed. As a result, an intelligent system, namely a fuzzy logic production model of deviant behavior of minors "Deviance level BD", has been created, which can be used to prevent deviant behavior in minors, as well as to analyze and identify manifestations of their aggressive behavior to prevent them from committing criminal acts.

1. Gulyaeva K.U. Aggressiveness in adolescence and its correction. Omskij nauchnij vestnik = Omsk Scientific Bulletin. 2007;55(3):107–110. (In Russ).

2. Buss A.H., Perry M. The Aggression Questionnaire. Journal of Personality and Social Psychology. 1992;63(3):452–459. DOI: 10.1037//0022-3514.63.3.452.

3. Uzlov N.D. Declared aggressivity of law-abiding citizen and convicts with various prison terms, diagnosed by Buss-Durkee hostility inventory. Vestnik Permskogo universiteta = Perm University Herald. 2014;18(2):100–110. (In Russ).

4. Narushev I.R., Melnikov A.V., Denisenko V.V. Models of the generalized indicator of deviant behavior of minors. Vestnik Voronezhskogo instituta MVD Rossii = The bulletin of Voronezh Institute of the Ministry of Internal Affairs of Russia. 2018;(1):44–50. (In Russ).

5. Leonenko A.V. Fuzzy modeling in MATLAB and fuzzyTECH. Saint Petersburg, BKhV-Peterburg; 2005. 736 p. (In Russ).

6. Shevchenko I.V., Karmazin V.N., Kovalenko A.V. Comprehensive assessment of the creditworthiness of small and medium-sized businesses using a fuzzy production system. Finansovaya analitika: problemy i resheniya = Financial Analytics: Science and Experience. 2008;2(2):81–86. (In Russ).

7. Kovalenko A.V., Karmazin V.N. Diagnostics of the state of the enterprise based on fuzzy production systems. Trudy Kubanskogo gosudarstvennogo agrarnogo universiteta = Proceedings of the Kuban State Agrarian University. 2008;2(11):20–27. (In Russ).

8. Kovalenko A.V. Neural network and fuzzy logic sets as a tool for assessing the creditworthiness of the borrower. Applied mathematics of the XXI century. Proceedings of the 5th Joint Scientific Conference for students and postgraduates of Applied Mathematics Department. 2006:56–58. (In Russ).

9. Khvan A.A., Zaitsev Yu.A., Kuznetsova Yu.A. Standardization of the questionnaire by A. Buss and A. Darkee. Psikhologicheskaya diagnostika. 2008;(1):35–58. (In Russ).

10. Nedosekin A.O. Financial management on fuzzy logic sets. Audit and financial analysis = Audit i finansovyi analiz. 2003;(3):195–255. (In Russ).

11. Kirillova E.B. Gender differences in personality traits of juvenile convicts. Vestnik of the St. Petersburgh University of the Ministry of Internal Affairs of Russia = Vestnik Sankt-Peterburgskogo universiteta MVD Rossii. 2017;74(2):201–206. (In Russ).