Simulation Daily Mobility in Rabat Region Using Multi-Agent Systems Models

Authors

  • Khalid Qbouche LRIT associated unit to CNRST (URAC∘29), Faculty of Science, Mohammed V University in Rabat, 4Av.Ibn Battouta B.P. 1014 RP, 10006 Rabat, Morocco
  • Khadija Rhoulami DESTEC, FLSHR Mohammed V University in Rabat, Morocco

DOI:

https://doi.org/10.13052/jicts2245-800X.10210

Keywords:

Markov Chain Model, Bayesian Belief Networks, Gama Platform, Multi-Agent System, Daily Mobility

Abstract

Due to the rapid urbanization of the world, the issue of daily movement has become an important topic. It examines the daily movements of people and analyzes the behavior of individuals. This system is closely related to the urban area, especially traffic. This work will provide a mixed model of daily mobility and a person’s shifting condition. Bottom-up techniques, such as Markov Chain and Multi-agent Systems, allow the creation of individual or group displacements. Bayesian Belief Network combined with Markov Chain allow for designing and managing individual behavior displacements.

Downloads

Download data is not yet available.

Author Biographies

Khalid Qbouche, LRIT associated unit to CNRST (URAC∘29), Faculty of Science, Mohammed V University in Rabat, 4Av.Ibn Battouta B.P. 1014 RP, 10006 Rabat, Morocco

Khalid Qbouche obtained the bachelor’s degree in mathematics and computer science from the faculty of sciences of Rabat in the kingdom of Morocco, the Mohamed V University of Rabat in 2015, and also obtained a master’s degree in computer science, option Computer Science and Telecommunications Multimedia Content at the Faculty of Sciences of Rabat in 2018. Currently, i am a doctoral student at the Faculty of Sciences of Rabat in a research laboratory in computer science and telecommunications.

Khadija Rhoulami, DESTEC, FLSHR Mohammed V University in Rabat, Morocco

Khadija Rhoulami Professor of computer science, Mohammed V University, Faculty of Letters. I am a member of the laboratory of computer science and telecommunications research, which belongs to the Faculty of Sciences of Mohammed V University in Rabat, Morocco. I have several scientific publications in the field of computer systems

References

K. Qbouche, K. Rhoulami, (2021). Simulation Daily Mobility in Rabat region. 10.1145/3454127.3454128.

K. Verda, D. Suzana. (2012). Bayesian networks and agent-based modeling approach for urban land-use and population density change: A BNAS model. Journal of Geographical Systems. 15. 10.1007/s10109-012-0171-2.

A. Ersin, Ö. Merve, B. Rüya and Y. Mutlu. (2020). Eskişehir Kentsel Büyüme Alanın Hücresel Otomat ve CA-Markov Zincirleri ile Analizi (1984-2056).

G. Sebastien, K. Marc-Olivier, N. Miguel. (2012). Next Place Prediction using Mobility Markov Chains. Proceedings of the 1st Workshop on Measurement, Privacy, and Mobility, MPM’12.10.1145/2181196.2181199.

K Qbouche, K Rhoulami. (2022) Towards for an Agent-Based Model to Simulate Daily Mobility in Rabat Region. In: Saidi R., El Bhiri B., Maleh Y., Mosallam A., Essaaidi M. (eds) Advanced Technologies for Humanity. ICATH 2021. Lecture Notes on Data Engineering and Communications Technologies, vol 110. Springer, Cham. https://doi.org/10.1007/978-3-030-94188-8_1.

Institutional site of the High Commission for Planning of the Kingdom of Morocco https://www.hcp.ma/.

H. Rfah, S. Ariffin, S. Hafizah, F. Norsheila. (2016). Mobility prediction method for vehicular network using Markov chain. Jurnal Teknologi. 78. 10.11113/jt.v78.8885.

A. Giret, V. Botti. (2021). Multi Agent Systems of Multi Agent Systems.

Monti, Stefano, and Gregory F. Cooper. “Learning Bayesian belief networks with neural network estimators.” Advances in Neural Information Processing Systems (1997): 578–584

An official website Gama Platform: https://gama-platform.github.io/.

N. Tuan, B. Alain, E. Pascal. (2012). Multi-agent Architecture with Space-time Components for the Simulation of Urban Transportation Systems. Procedia - Social and Behavioral Sciences. 54. 365–374. 10.1016/j.sbspro.2012.09.756.

J. Agbinya. (2020). Markov Chain and its Applications an Introduction.

Downloads

Published

2022-05-21

Issue

Section

Intelligent Systems for Smart Applications