Using the particle swarm optimization for geoid determination

Abstract

Geoid determination is the modelling that enables us to determine the height of a point whose position is known. Geoid determination has made important problem of Geodesy with GPS technologies. One of the important points when determining the geoid is to select the outlier points in the data set. These points named as outlier measurements. These points are determined by the outlier measurements test. There are many different methods used in the literature to determine outlier measurements. The most widely used of these is The Least Square Method (LS). Also nowadays, very complex problems can be solved with methods such as the rapidly developing Artificial Intelligence and Machine Learning Technologies with Metaheuristic Algorithm for obtaining a close to optimum solution. One of these algorithms is Particle Swarm Optimization. In this study, the usability of the particle swarm optimization was tested to determine the outlier measurement in the geoid determination process.