Heuristic decision making selection of drone models according to specified characteristics - V. V. Afonin; V. V. Nikulin (Вестник Дагестанского государственного технического университета: Технические науки, 2024)
Objective. The noticeable interest in aircraft such as drones for various purposes puts forward certain requirements for their characteristics. Characteristics can be divided into information technology and consumer characteristics from a financial point of view. At the same time, they have their own units of measurement. In this regard, the task of selecting and ranking drones according to some criterion or numerical metric arises. Considering that this problem is quite relevant, this paper considers a certain heuristic approach to sorting a sample of drones by the key of the proposed metric.Method. In the heuristic approach, there is a certain variability in determining the attractiveness of a particular drone in the opinion of the person making the decision to purchase or a specific choice from the existing line of drones available for review based on their characteristics.Result. It is proposed to identify several groups in the existing characteristics, heterogeneous in their properties, both obvious and intuitively created: “good”, “very good”, “less attractive”, “least attractive”. Assuming that several models of drones with the same characteristics are being considered, divided into the specified groups, numerical coefficients are introduced to form a metric by which a given line or selection of drones will be ranked according to the calculated metrics.Conclusion. The proposed heuristic algorithm is based on the transition to the reduced values of numerical characteristics relative to the maximum of each group of characteristics with the calculation of the arithmetic mean of the given values. Depending on the type of specified groups, the coefficients entered into consideration are added or subtracted from the difference between the current characteristic and its average or the difference between the average and the current characteristic. On this basis, metrics are calculated by which the given sample of drone models is ranked.