الفهرس 
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Abstract
Bridges are playing a major role in the socio-economic development of cities. In the world there are about 250000 bridges that require surveys, and the state of their designs must be subject to periodic and systematic monitoring. Cable-stayed bridge due to their design features is the most sensitive to various external influences. So that, for the special engineering structures it is important to choose the method of regular monitoring of critical points. Today global navigation satellite systems (GNSS) have become an alternative to the classical geodetic methods, often ahead of them in terms of accuracy and cost effectiveness. The great advantage of GNSS monitoring is its continuous operation in real time. The study examined the monitoring of cable-stayed bridges, taken into consideration the impact on the nature of the deformation of wind, temperature, humidity and traffic loads during the operational and short-term measurements. An important element of monitoring is necessary to predict. Due to the complexity of the mathematical processing of large data GNSS monitoring for obtaining reliable results should be choose the most adequate model of several alternatives. Artificial neural networks (ANN), which is using a confidence interval with a probability of p = 0.95, Δ = ± 2σ gets a correlation coefficient of 0.96. It proved an advantage for a reliable assessment of both kinematics and dynamics of the observed object.