Simulation Daily Mobility using J48 Algorithms of Machine Learning for Predicting Workplace

Khalid Qbouche, Khadija Rhoulami

2021

Abstract

Nowadays, the urban development of the city has led to changes in various fields, such as population growth and its daily various activities. These activities have been influenced by the development, concerning either air, water, or land mobility. Mainly, human mobility is defined in terms of it. This latter fact makes it easy for researchers to gain realistic insights for a rational simulation of human mobility in general and workplace-related mobility in particular. More precisely, this paper will focus on j48 algorithms of Machine Learning to predict a potential workplace, and in parallel to this, a tiny Multi-Agent system will be useful to simulate the Rabat region's main traffic

Paper Citation

in Harvard Style

Qbouche K. and Rhoulami K. (2021). Simulation Daily Mobility using J48 Algorithms of Machine Learning for Predicting Workplace. In Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML, ISBN 978-989-758-559-3, pages 392-398. DOI: 10.5220/0010735200003101

in Bibtex Style

@conference{bml21,
author={Khalid Qbouche and Khadija Rhoulami},
title={Simulation Daily Mobility using J48 Algorithms of Machine Learning for Predicting Workplace},
booktitle={Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,},
year={2021},
pages={392-398},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010735200003101},
isbn={978-989-758-559-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Big Data, Modelling and Machine Learning - Volume 1: BML,
TI - Simulation Daily Mobility using J48 Algorithms of Machine Learning for Predicting Workplace
SN - 978-989-758-559-3
AU - Qbouche K.
AU - Rhoulami K.
PY - 2021
SP - 392
EP - 398
DO - 10.5220/0010735200003101