Abstract
The object of research is development of a method for finding a safe position for military units in combat conditions, using swarm algorithms and neural networks. One of the most problematic places is the complexity of testing the developed method. The difficulty lies in the fact that to check the method in real time, financial costs and military weapons are necessary.The data are obtained due to a multicriteria problem, which allowed to calculate the errors of subjects and objects of research.The obtained results show that the hybrid method allowed to calculate the safe position with greater accuracy, namely by 25–50 % more accurately than using the classical approach. This is due to the fact that the proposed method calculates all possible errors.This makes it possible to obtain the flexibility of the method for finding a safe position. In comparison with the analogous methods known in the formulation of the classical problem of calculating the trajectory and the damage region, only one mathematical value (region, trajectory) is taken into account, and using a hybrid approach one can take into account a number of errors simultaneously. This approach ensures the flexibility of the system and the possibility of expanding a number of mathematical calculations and improving the accuracy of the result.
Highlights
A well-known fact is that with the development of technologies, the needs of mankind are increasing
Swarm algorithms used in developing various me thods and mathematical models of military problems are effective [1–3]
In constructing a multicriteria task and developing a mathematical model for the search for a safe position of military units in hazardous areas, a number of issues are resolved: 1) determination of the characteristics of participants in the process according to the data inherent only to them; 2) calculation of errors is carried out at the prev ious stage, that is, they are set in the construction of a multi criteria problem; 3) flexibility parameter of the algorithmization of this process is taken into account
Summary
A well-known fact is that with the development of technologies, the needs of mankind are increasing. Swarm algorithms used in developing various me thods and mathematical models of military problems are effective [1–3]. Neural networks are widely used in the modern world through their adaptability to the tasks of a different plan. Their feature is that neural networks are a network of artificial cells, which in turn have memory [3–7]. This property can be used in different directions, inclu ding in the construction and solution of transport-type problems. An important step in designing the search process for the safe position of the fire potential is the calculation of optimization of the technical and economic characteristics of parameters using the swarm algorithms. Most combat operations are carried out remotely, so it is timely to identify the enemy’s position with its own shots or other aggressive actions
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