Designing an expert system based on Rough Theory to predict the group dynamics of employees based on their emotional intelligence

The welfare organization needs employees with high emotional intelligence to be able to perform their duties effectively; Therefore, predicting the group dynamics of employees based on their emotional intelligence in the Welfare Organization of Mazandaran Province was the purpose of this study.The statistical population of the present study was 1125 employees of the Welfare Organization of Mazandaran Province. The number of statistical sample was considered to be 290 people.The research measurement tool was standard questionnaires of Bar-On emotional intelligence and researcher-made intergroup dynamics. In order to analyze the data, model, the theory of Rough set Theory has been used. With the help of Rough Theory, the level of group dynamics of employees as a decision characteristic and seven situational characteristics as a decision system have been entered into ROSETTA software and the rule model has been extracted. According to different algorithms of discretization and redundant production, eight models of rules were constructed and the results of each model were evaluated by parallel validation method. The results show that the level of education and interpersonal dimensions and adaptability have the greatest effect on group dynamics. the best model has been selected using entropy discretization method, genetic algorithm and ORR strategy for redundant production, with 434 rules and 77.83% prediction accuracy. The model of rules was selected with the highest validity as the inference engine of the expert system and after designing the user interface, it was possible to predict the group dynamics of employees by examining their level of emotional intelligence