Vehicular swept path analysis using K-means algorithm

Abstract:

The aim of this work is to obtain a set of data clusters to present GPS vehicle trajectories. In this matter, the clustering algorithm instantiation on k-means data provided by the WEKA tool in the process of data mining is used. A sample of 50 vehicle paths from" the century mobile field experiment" data set, to perform data mining techniques extracted; the proposed work began to process this information in the database object relational PostgreSql. Furthermore, to the vehicle paths were implemented a script to work with a column of geometrical point and time specified during monitoring of travel of each vehicle. Finally the clustering algorithm SimpleKmeans of WEKA was used to display the different paths and collect the results.

Año de publicación:

2016

Keywords:

• clustering
• data mining
• Kmeans algorithm
• Vehicular trajectory
• WEKA

Fuente:

scopus

google