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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