A Study on Spatial Prediction Models and Influential Parameters of Deformation in Western Ireland

This paper attempts to estimate the deformation status for certain geographic points in the western areas of Ireland. We used a ground motion service dataset (EGMS), applying key features related to the deformation value to analyze their importance. We used random forest analysis on the data set to check the significance of these characteristics. We also applied several machine learning methods to train the dataset to find out whether we can use these data to get a proper estimate. Our findings demonstrate that it is difficult to estimate the state of deformation on certain points using spatial features of other points. Normally formed values show better relativity than STD formed values. This research offers valuable insights, and provides an example of the deformation status estimation. The study encourages future investigation into temporal analysis approaches, using time-series provided in the dataset to enhance estimation accuracy.