Optimization of the algorithm of decision making support systems for the work based on a fuzzy decision tree

Abstract

The material of the article is aimed at solving urgent scientific, economical and macro-problems оf the forecasting. The necessity to build a fuzzy decision tree is based on the analysis of mathematical techniques that proved its feasibility. In this article we propose to use the algorithm of methods for solving certain problems in the decision tree. The present materials examines issues of process optimization forecasting methods by using fuzzy decision support system. In the article we show how we can successfully make the architecture, algorithm, and practically realised composition program-technical system used to obtain sufficiently accurate results in prediction of macro-parameters. Although the model is adapted to solve the problem prediction of macro parameters, but it can be used for analysis and forecasts of other financial phenomena that resist explanation by the classic interplay of economic indicators. In our article we will consider: the mechanism of decision making support system (DMSS), universal mathematical model for DMSS in prediction of economic macro-parameters. We will propose the certain scheme of using different algorithms for decision making support system. We will make recommendations concerning how to make self educational prediction model and show the necessity of non-stop upgrading knowledge bases of the model depending on different economical situations.