Using data mining to improve the public transport in Gran Canaria Island

Abstract

In this work Business Intelligence and Data Mining techniques have been used to extract useful knowledge for the main corporation of intercity public transportation on Gran Canaria island. The aim has been to find a pattern to predict the number of passengers who want to travel from one point to another. To achieve it, events files generated in the vehicles of the company and additional data have been used as information source: temporal (time of the trip, type of the day,month and season) and geographic and demographic (departure and destination bus stop, type of bus stop and zip codes of the origin and destination bus stop.