Comparativa de diferentes técnicas de Minería de Datos para la predicción del uso de la bicicleta de acuerdo con las condiciones climáticas y estacionales en Washington

Ana Rosa Velazquez; Francisco Jacob Avila Camacho

doi:10.2992/rict.v2i3.44

Authors

Ana Rosa Velazquez Tecnologico de Estudios Superiores de Ecatepec
Francisco Jacob Avila Camacho Tecnológico Nacional de México / TES Ecatepec https://orcid.org/0000-0002-0086-5827

DOI:

https://doi.org/10.2992/rict.v2i3.44

Keywords:

Prediction, regression trees, Neural networks, regression, machine learning

Abstract

In this article we worked with the prediction of bicycle rental per day, focused on environmental and seasonal conditions, a comparative analysis was carried out between two data mining techniques: regression trees and traditional regression. The data set was taken from the Capital Bikeshare system in Washington D.C. During the years 2011 and 2012, it provided a detailed historical record of the days and seasons of the year, enriched with meteorological information and the number of registered users.

The choice to compare regression trees with classical regression was based on the need to evaluate which of these techniques best suited the complexity of the data set and the nonlinear nature of the relationships between both the dependent and independent variables.

Author Biography

Francisco Jacob Avila Camacho, Tecnológico Nacional de México / TES Ecatepec

Francisco Jacob Avila-Camacho. He was born in Puebla, Mexico on February 5, 1967, he is an electronics and digital systems engineer graduated from the Universidad Autónoma Metropolitana Azcapotzalco Unit, he has a master's degree in computer systems engineering from the Tecnológico de Estudios Superiores de Ecatepec, he has a master's degree in science in business administration from the Higher School of Commerce and Administration of the IPN and a doctorate in computer systems from the Da Vinci University, he currently works as a research professor at the Technological Institute of Higher Studies of Ecatepec, has given presentations at congresses national and international and published in magazines and conference proceedings, he is currently responsible and leader of several research and technological development projects with and without financing, Coordinator of the TESE Industry Academy Cooperation Center. His main lines of research focus on artificial intelligence, pattern recognition, data mining and embedded systems, autonomous navigation models and algorithms, computer vision, among others.

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