On the issue of sensitivity analysis of system parameters of transport and technological cycles of UAVs

The article is devoted to the sensitivity analysis of system parameters of UAV transport and technological cycles under uncertainty caused by the diversity of operating environments (precision agriculture, mining, logistics, etc.) and the interdependence of system parameters. The limitations of classical sensitivity analysis methods based on variance assessment are noted, as applied to models with interrelated parameters, such as operation execution time and required resources. It is shown that traditional approaches that are effective for independent variables require modification to account for nonlinear dependencies characteristic of UAV transport and technological cycles. The methods for improving sensitivity analysis methods are proposed, including the introduction of correction factors, multi-criteria optimization, and integration with artificial intelligence algorithms. This will improve the accuracy of forecasting the cycle implementation time and optimize resource provision, which is important for decision makers in conditions of limited information. The role of sensitivity analysis in assessing microprocessor performance, distributing computing resources, and integrating pattern recognition systems into UAV onboard equipment is noted. The need to develop specialized analysis methods adapted to the specifics of UAV transport and technological cycles is substantiated.