Інформаційна технологія підтримки прийняття групових рішень у розподілених системах

Abstract

The thesis is dedicated to the study of increasing the effectiveness of group decision support in distributed systems. Information technology to support group decision-making has been developed, which allows to increase the speed of group decision making while maintaining their reliability, as well as to train the decision makers at the same time. An information model of a distributed group decision support system has been developed, which allows to combine all elements of a distributed system and provides an opportunity to influence the initial probabilities of alternative decision-making by introducing current user preferences. A method for preparing data for group decision-making using a Bayesian network is proposed, which allows to form alternatives for user selection by statistical analysis of the training sample, which allows to increase the efficiency of group decision-making by offering the most likely initial alternatives for user selection. A dynamic Bayesian network for the formation of user choice alternatives is proposed, which uses a priori probabilities of alternatives and is dynamically updated during each stage of user decision-making, which allows to offer the most probable alternatives at each stage of user decision-making until all alternatives are completed.