Improvement of the method of parametric control of the state of the control object based on the improved firefly algorithm

The problem that is solved in the study is to increase the efficiency of decision-making regard-ing the state of the control object while ensuring a given reliability, regardless of the object’s hierarchy. The object of the study is deci-sion support systems. The subject of the study is the process of assess-ment and parametric control of the state of the control object using the firefly algorithm. The hypothesis of the study is an increase in the effi-ciency of assessing the state of the control object with a given reli-ability. In the course of the study, an improved method of parametric control of the control object based on the improved firefly algorithm was proposed. General provisions of artificial intelligence theory were used for solving the problem of object state analysis and subse-quent parametric control in intelli-gent 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 control object (complete uncertainty, partial uncertainty and complete awareness); −taking into account the noise of data on the state of the control object. Data noise refers to the degree of information distortion created by the enemy’s electronic and cyber warfare; −using the improved firefly algorithm to find the path metric while assessing the state of the control object;−deep learning of the synthesized ants using evolving artificial neural networks.The application of the pro-posed method is presented on the example of assessing the state of the operational situation of a group of troops(forces). The spe-ified example showed a 17–20% increase in the efficiency of data processing using additional improved procedures