Common Movement Prediction using Polynomial Regression
Timur Bakibayev, Akbota Kulzhanova · 2018
This paper describes an algorithm for geographical coordinates processing using polynomial regression to calculate the common behavior of a movement. The primary advantage of this algorithm is having a map of trajectories in any region. We have used Python programming language together with scikit-learn and matplotlib libraries for machine learning and visualization. In the end we try to predict several steps of the movement of all objects on the map.This work is the result of Master Thesis research.