Abstract
One of the main subjects of Geodesy is the monitoring of position changes of artificial structures (buildings, dams, bridges etc.). Such position changes can be caused by a variety of reasons such as vehicles for cable bridges and earthquakes. Various mathematical models have been developed in order to monitor and to analyze this phenomenon. This study presents the main models which are used by geodesists for the description of points’ displacements. These are the descriptive models (which are separated into the congruence and the kinematic ones) and the cause-response models (which are separated into the static and the dynamic). Moreover, several models, which are based on time series analysis and are used mainly for the prediction of financial parameters, are referred in parallel. These are the smoothing models, the time series decomposition models, and the ARIMA models. All the abovementioned models are discussed and compared in order to emerge their advantages, disadvantages, and limitations. The goal of this study is to substantiate which of these models could be used with reliability for prediction of displacements. A case study using the most appropriate models is carried out. The experiment deals with the prediction of displacements of a set of permanent GNSS stations. The results proved that the linear kinematic models have the best performance, in comparison with the other examined models.
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Alevizakou, EG., Pantazis, G. A comparative evaluation of various models for prediction of displacements. Appl Geomat 9, 93–103 (2017). https://doi.org/10.1007/s12518-017-0189-8
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DOI: https://doi.org/10.1007/s12518-017-0189-8