Development of decision support methods under uncertainty

Abstract

The article analyzes economic and mathematical models and methods of decision support under uncertainty. National and foreign experience of economic situations related to the dissemination of knowledge has been studied, and the main aspects of the knowledge economy have been identified. Methods of knowledge representation are considered, in particular, the rules for building a production model of knowledge are defined. The analysis of intelligent systems based on learning and self-learning (with a “teacher”, without a “teacher”) is carried out and it is concluded that to assess economic processes, it is necessary to consider a set of techniques related to poorly formalized tasks, which include economic tasks.The methodological base of the research includes the fuzzy control method, the Saati method, and the Bayesian Belief Network method, which are the basis of the developed economic and mathematical model. The theoretical and practical significance of the study is to justify the need to develop a comprehensive assessment of the efficiency of a mobile application.JSC “SKB-Bank” was selected as the research object, the subject of this study is to develop an additional module “Conducting financial card transactions of JSC ‘SKB-Bank’ ” mobile app.The effectiveness of the development was evaluated, in particular during the development of the module “Conducting financial card transactions of JSC ‘SKB-Bank’ ” of the mobile application. To do this, we defined metrics that served as criteria for determining the effectiveness of the project, as well as project risks that were estimated based on the theory of fuzzy sets. The developed methods of decision support under uncertainty allowed us to draw a conclusion about the efficiency of the project as a whole. The developed model can be used to evaluate the efficiency of mobile applications for any company.