| Issue |
MATEC Web Conf.
Volume 295, 2019
Smart Underground Space and Infrastructures – Lille 2019
|
|
|---|---|---|
| Article Number | 02002 | |
| Number of page(s) | 5 | |
| Section | Resilient Infrastructures | |
| DOI | https://doi.org/10.1051/matecconf/201929502002 | |
| Published online | 18 October 2019 | |
Comparison of M5 Model Tree and Nonlinear Autoregressive with eXogenous inputs (NARX) Neural Network for urban stormwater discharge modelling
1 Laboratoire de Génie Civil et géo-Environnement, Université de Lille, 5900 Lille, France
2 Laboratoire d’Analyse des Systèmes, Traitement de l’Information et Management Industriel, Université Mohammed V, Rabat, Morocco
3 National Higher School of Mines, Agdal Rabat, Morocco
This paper presents a comparative study of two data-driven modelling techniques in forecasting urban drainage stormwater discharge based on rainfall prediction. Both M5T and NARX (Nonlinear Autoregressive with eXogenous inputs) Neural Network are used for 30 minutes storm water forecasting. Data are collected from watershed area of 3315 ha, located in the city of Casablanca in Morocco. The results show that both models provide good results, but however with better performances of the NARX model.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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