METHOD FOR PREDICTING THE FLIGHT PATH OF LONG-RANGE UNMANNED AERIAL SYSTEMS BASED ON THE ELITE ANTS ALGORITHM
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Abstract
The subject matter of the article is a method for predicting the flight path of long-range unmanned aerial systems based on the elite ants algorithm. The goal is to develop a method for predicting the flight path of long-range unmanned aerial systems. The tasks are: analysis of existing methods for laying flight paths, development of a method for predicting the flight path of long-range unmanned aerial systems based on the elite ant algorithm, practical verification of the operation of the developed method, conducting experimental studies on predicting the flight path of movement using the method based on a simple ant algorithm and based on the elite ant algorithm, conducting a comparative analysis of the obtained experimental results. The methods used are: graph modeling, multi-criteria optimization, simple ant algorithm, ant algorithm based on elite ants, computer modeling, and comparative analysis of results. The following results are obtained. The methods of laying flight paths are analyzed depending on the approach to optimization, taking into account the specified flight restrictions. They are divided into four main groups, and their main advantages and disadvantages are determined. We will give a formal description of the problem of predicting the path of long-range unmanned aerial systems based on the ant algorithm. A simple ant algorithm and an elite ant algorithm are considered. A method of predicting the path of long-range unmanned aerial systems based on the elite ant algorithm is developed. Experimental studies are conducted on the operation of the method of predicting the path of long-range unmanned aerial systems. A comparative assessment of the efficiency of the simple ant algorithm and the ant algorithm based on elite ants in solving the problem of predicting the optimal path of long-range unmanned aerial systems is carried out. Conclusions. Analysis of experimental studies showed that the use of the elite ant algorithm is more appropriate for the task of predicting the flight path of long-range unmanned aerial systems. The direction of further research is to optimize the input parameters of the elite ant’s algorithm to solve the problem of predicting the flight path of long-range UASs in order to increase its accuracy and stability.
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