Аннотации:
Many natural processes in space may be simulated and controlled by a computer using the corresponding methods and approaches. These processes include: Geophysical phenomena, gravitational interactions, celestial bodies mechanics, and astrophysical events. In these cases, computer simulation directly interactswith physical systems. As it is well known, thosemodels refer to cyber-physical systems (CPS). In the case of geophysical processes, there is the interaction between computer algorithms and complex physical systems, whosemodels are hard to develop and control. The practice of analyzing geophysical processes has shown one is able to control the behavior of such systems using the computer adaptive regression modeling which also allows performing prediction actions. The construction of the prediction dynamics of a physically complex system has a crucial value for the quality of processing geophysical information. At the same time, CPS could be complex, especially when it is necessary to combine cyber-physical systems. The application of adaptive regression modeling for analyzing geophysical parameters is considered. In this chapter, the variations of the Earth’s pole position are investigated. Based on time series of observations of the Earth’s pole an adaptive regression model (ARM) describing the pole’s dynamics over 30 years is developed. Similar models were created earlier by other authors but their capabilities were limited for prediction. The ARM approach has provided a more accurate combination of observational and model parameters. As a result, the use of ARM has allowed constructing the predictive curve of the change in the Earth’s pole motion and comparing the produced results with observations. The comparison shows a rather good agreement between the model parameters and the observations data.
