Methodical approach to increase the speed of decision-making in information systems

Abstract

The relevance of the research lies in the need to increase the efficiency of the process of evaluating the object of evaluation while ensuring the given reliability, regardless of the hierarchical construction of the object of evaluation. The object of research is information systems. The subject of the study is the efficiency of the evaluation process. The hypothesis of the study is to increase the efficiency of the process at a given reliability. In the study, an improved methodology for increasing the efficiency of the evaluation process based on bio-inspired algorithms was proposed. In the course of the conducted research, the general provisions of the theory of artificial intelligence were used to solve the problem of analyzing the state of objects in intelligent decision support systems. The essence of improvement is to use the following procedures: − taking into account the type of uncertainty about the state of the object of evaluation; − taking into account the degree of the noise of the data on the state of the object of evaluation; − using the ant algorithm and the genetic algorithm to find the path metric when evaluating the state of the evaluation object; − deep learning of synthetic ants using evolving artificial neural networks. An example of the use of the proposed methodology is presented in the example of the assessment of a hierarchical object. The specified model showed a 15−22 % increase in data processing efficiency due to the use of additional improved procedure