Abstract
The object of the research is intelligent decision-making support systems. The scientific problem that is solved in the research is the development of a comprehensive model for processing various types of data in intelligent decision-making support systems (DMSS). The relevance of the research lies in the fact that in intelligent DMSS circulate different in origin and units of measurement data obtained from various technical devices of obtaining information. The essence of the integrated approach in modeling is that two partial models are proposed: a model for processing different types of data in intelligent decision-making support systems and a model for processing homogeneous data in intelligent decision-making support systems. Analysis of the intelligent DMSS model for processing different types of data allows to draw such a conclusion. While solving the problem of processing different types of data, a model of intelligent DMSS is proposed, in contrast to traditional, even for the process of solving partial problems incorrectly started by experts with the help of self-organization, expressed in the coordination of partial tasks of the decision maker, striving for an ideal solution to the problem of processing different types of data, which increases the efficiency of finding an acceptable result for processing different types of data. The homogeneous data processing model is based on the idea that the same processing of homogeneous data in intelligent DMSS can be solved in parallel by different functional elements. Element integration relationships arise as internal non-verbal images in the user's memory, which can compare the dynamics of modeling a task for processing different types of data in intelligent DMSS from different points of view, which allows to see what modeling does not give using one model. The direction of further research should be considered the improvement of information processing methods in intelligent decision-making support systems.
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