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DOI: 10.18413/2408-9338-2018-4-3-0-7

STATISTICAL MODELING AND ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN THE ASSESSMENT AND MANAGEMENT OF THE PARAMETERS OF A SINGLE CREATIVE TEAM FIELD: THE EXPERIENCE OF QUANTITATIVE ANALYSIS

The article discusses the issues related to the modeling of the processes of formation and management of team work, including the parameters of a single creative field of project teams. A brief analysis of the existing social situation and models used in social research is given, their strengths and weaknesses are considered. A short list of sociological methodological approaches, theoretical and methodological tools is given. The results of specific socio-psychological experiments related to the formation and evaluation of the parameters of a single creative field are presented. A system of statistical, dynamic/simulation and expert-analytical models of predictive analytics necessary for effective management of project teams is proposed, a brief description of its levels and their parameters is given. The authors carry out the quantification of the main parameters of a single creative field (organizational, cognitive and affective) of project teams. Suggestions for improving the technology of DSM-method of plausible reasoning are given.

Figures

Рис. 1. Пятиуровневая иерархическая система моделей информационно-аналитического обеспечения управления командами

Fig. 1. Five-level hierarchical system of models of information and analytical support
for team management

Рис. 2. Диаграмма сходимости уравнения 3

Fig. 2. The diagram of convergence of equation 3

Рис. 3. Диаграмма сходимости уравнения 4

Fig. 3. The diagram of convergence of equation 4

Рис. 4. Основной алгоритм ДСМ-метода

Обозначения: F – матрица исходных данных (фактов); H – матрица гипотез о возможных причинах; F’ – доопределенная матрица исходных данных; CSR – правила поиска причин (правила первого рода); DDR – правила доопределения исходных данных
(правила второго рода)

Fig. 4. The main algorithm of the DSM method

Symbols: F – matrix of initial data (facts); H – matrix of hypotheses about possible causes;
F’ – predetermined matrix of initial data; CSR – rules for finding causes (rules of the first kind); DDR – rules for pre-determining the source data (rules of the second kind)

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