Previous issue (2020. Vol. 13, no. 3)
Included in Web of Science СС (ESCI)
|
|
Simple neuro network algorithms for evaluating latent links of younger adolescent’s psychological characteristics 337
Slavutskaya E.V.
Doctor of Psychology, professor of Psychology and Social Pedagogic department, Chuvash State Pedagogical University of I.Ya. Yakovlev, Cheboksary, Russia
e-mail: slavutskayaev@gmail.com Abrukov V.S.
Doctor of Physics and Matematics, Head of Department of Applied Physics and Nanotechnology, Chuvash State University, Cheboksary, Russia
e-mail: abrukov@yandex.ru Slavutskii L.A.
PhD in Physics and Matematics, Professor of the Automatics and Control department, Chuvash State University, Cheboksary, Russia
e-mail: lenya@slavutskii.ru
The artificial neural networks (ANN) for the psycho-diagnostics data analyzing is used. It is shown that the training of a simple ANN of direct propagation, as the problem of nonlinear multi-parameter optimization, allows to carry out the vertical system analysis and to assess the latent, non-linear relationship between different level’s psychological characteristics (the system of relationships, motivational characteristics, personality traits, intelligence, the type of nervous system). The detection of such links using the traditional for psychology the correlative ore factor analysis is difficult. Quantitative criteria are proposed for evaluating the quality of ANN algorithms, which are based on a scattering diagram and the statistical distribution of errors in the learning and testing of a neural network. As an example, the data of psycho-diagnostics of younger adolescents are analyzed. The proposed algorithms and criteria made it possible to detect latent links between psychological characteristics, to evaluate the ratio of psychological level-based indicators.
-
Abrukov V.S., Abrukov S.V., Smirnov A.V., Karlovich E.V.
Data mainin v naychnih issledovaniah [Data mainin in scientific researches].
Conference: Nanostructured materials and соnverting devices- NANOSOLAR-2013,
[Elektronnyi resurs] Cheboksary,
2013.//URL:https://www.researchgate.net/
publication/270452415_Data_mining_v_naucnyh_issledovaniah (Accessed:
17.09.2018).
-
Aksenov S.V., Novoseltsev V.B. Organizatsiya i
ispol’zovaniye neyronnykh setey (metody i tekhnologii) [Organization and use of
neural networks (methods and technologies)] / Pod. red. V.B. Novoseltseva.
Tomsk: Izd-vo NTL, 2001. 128 p.
-
Ananiev B.G. Chelovek kak predmet poznaniya [Man as an
object of knowledge]. Spb.: Piter, 2001. 288 с.
-
Arzamaszev A.A. Zenkova N.A. Modelirovanie v psihologii na
osnove iskysstvennih neironnih setei [Modeling in psychology on the basis of
artificial neural networks]. Tambov: IMFI im. Derzavina. 2003, 106 p.
-
Barabanchikov V.A. Sistemnii podhod v struktyre
psihologicheskogo poznania [The System Approach in the Structure of
Psychological Cognition] // Metodologia i istoria psihologii [Methodology and
History of Psychology]. 2007. Т. 2. V.1. рр.86—99.
-
Borovikov V.P. Neironnii seti. Metodologia I technologia
sovremennogo analiza dannih / Pod. red. V.P. Borovikova. M. : Goryachaiya
liniya-Telecom, 2008. 392 p.
-
Vorobev A.V. Obzor primeneniya matematicheskikh metodov
pri provedenii psikhologicheskikh issledovaniy [The review of mathematical
methods application in psychological researches]. // Psichologicheskie
issledovania: electronni naychyni gournal [Psychological research: electron.
sci. journal]. 2010. № 2. (10).
-
Golovey L.A., Rybalko Ye.F., Prokhorenko T.V. Psikhologiya
razvitiya. Khrestomatiya [Developmental psychology. Reader]. SPb.: Piter, 2001.
512 с.
-
Kniazeva T.N. Predpodrostkovyy vozrast kak problema
sovremennogo detstva [Preteen age as a problem of modern childhood] // Voprosy
psikhologii [Questions of Psychology]. 2011. № 6. С. 25—35.
-
Kruglov V.V., Borisov V.V. Iskustvennii neironnii seti.
Teoria i praktica [Artificial neural networks. Theory and practice]. M.:
Goryachaiya liniya — Telecom, 2002. 287 р.
-
Lomov B.F. Sistemnost’ v psikhologii : izbrannyye
psikhologicheskiye trudy [Systematic in psychology: selected psychological
works]. Voronezh: MODEK; Moskva: Moskovskiy psikhologo-sotsial’nyy institute,
1996. 384 с.
-
Polivanova K.N. Psikhologicheskiy analiz vozrastnoy
periodizatsii [Psychological Analysis of Age Periodization] //
Kul’turno-istoricheskaya psikhologiya [Cultural-Historical Psychology]. 2006. №
1. С. 26—31.
-
Slavutskaja E.V., Slavutskii L.A. Neirosetevoi analiz
vzaimosvyazi verbalnogo i neverbalnogo intellekta mladchih podrostkov [Neural
network analysis of the interrelation between verbal and nonverbal intelligence
of younger adolescents] // Psihologicheskii jurnal [Psychological journal].
2014. V. 35. № 5. pp. 48—56. (in Russian)
-
Slavutskaja E.V., Slavutskii L.A. Factornii analiz
vzaimosvyazi individyalno-psihologicheskih i lichnostnih haracteristik mladchih
podrostkov s yrovnem shkolnoi dezadaptatsii [Factor analysis of the
relationship between the individual psychological and personal characteristics
of younger adolescents with the level of school disadaptation] //
Eksperimentalnaya psihologiya [Experimental Psychology]. 2013. V. 6. №
4. pp. 40—51.
-
Tsukerman G.A. Perekhod iz nachal’noy shkoly v srednyuyu
kak psikhologicheskaya problema [The transition from primary to secondary
school as a psychological problem] // Voprosy psikhologii [Questions of
psychology], 2001. № 5. С. 19 — 34.
-
Elkonin D.B. Psikhicheskoye razvitiye v detskikh
vozrastakh. Izbrannyye psikhologicheskiye Trudy [Mental development in
childhood. Selected psychological works] / Pod red .D.I. Fel’dshteyna. M.:
Izdatel’stvo «Institut prakticheskoy psikhologii»; Voronezh: NPO «MODEK», 1997.
416 с.
-
Shendiapin V.N., Skotnikova I.G., Barabanchikov V.A.,
Tarasov V.B. Matematicheskoe modelirovanie uverennosti pri priniatii rechenia v
sensornikh zadachakh [Mathematical modeling of confidence in decision- making
in sensory tasks] / Psychological Journal [Psychological journal]. Т. 29. № 4.
2008. pp. 84—97.
-
Baxt W.G. Complexity, chaos and human physiology: the
justification for non-linear neural computational analysis // Cancer Lett,
1994. Vol. 77. № 2—3. P. 85—93.
-
Berebin M.A., Pashkov S.V. Neural networks models usage
experience for psychic de-adaptation prediction [Opit ptimenenia neirosetevykh
modelei v tselayakh prognosa fizicheskoi desadapratsii] Veatntk YurGV
(The South Urals State University Bulletin), 2006. № 14. P. 41— 45.
-
Cattell R.B. Advanced in Cattelian Personality
Theory. Handbook of Personality. Theory and Research. N.Y.: The Guilford Press,
1990.
-
Collins W.A. (ed.) Development during middle childhood:
The years from six to twelve. Washington, DC: Natl. Acad. Press, 1984.
-
Dogic S., Karli G. Sign Language Recognition using Neural
Networks // TEM Journal, 2014. 3 (4). P. 296—301.
-
Haykin S. Neural networks: A comprehensive Foundation. New
York: Prentice Hall, 1999.
-
Hebb D. Organization of behavior. New York: Science
Edition, 1961.
-
Lipsitz J.S. Growing up forgotten: A review of research
and programs concerning early adolescence. Toronto: Lexington Books,
1977.
-
Lorenz V.A, Gavnkov V.L., Khlebopros R.G. Errors level
discretisation during the neural network teaching [Diskretizatsiva urovnya
oshibok pri obuchenii nejronnoi seti] Vestnik KGPU (Bulletin of KSPU).
Krasnoyarsk, 2012. N 3. P. 93—100.
-
Rosenblatt R. Principles of neurodynamics. New York:
Spartan Books, 1959.
-
Reznichenko N.S., Shilov S.N., Abdulkin V.V. Neuron
Network Approach to the Solution of the Medical- Psychological Problems and in
Diagnosis Process of Persons with Disabilities (Literature Review) // Journal
of Siberian Federal University. Humanities & Social Sciences, 2013. V. 9
(6). P. 1256—1264.
-
Slavutskaya E., Nikolaev E., Ivanova G., Yusupov I. Gender
Characteristics Of Junior Adolesents’ Personal Traits // The European
Proceedings of Social & Behavioural Sciences. ECCE 2018 [Электронный
ресурс] // URL: https://doi.org/10.15405/epsbs.2018.07.69 (дата обращения:
17.09.2018).
-
Usher M., Zakay D. A neural network model for
attribute-based decision processes // Cognitive Science.1993, V. 17. P.
349—396.
|
|
