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Boumédiène Derras
Boumédiène Derras
Full professor of Civil Engineering, https://www.univ-saida.dz/
Verified email at univ-tlemcen.dz
Title
Cited by
Cited by
Year
Towards fully data driven ground-motion prediction models for Europe
B Derras, PY Bard, F Cotton
Bulletin of Earthquake Engineering 12 (1), 495-516, 2014
1552014
Adapting the neural network approach to PGA prediction: An example based on the KiK‐net data
B Derras, PY Bard, F Cotton, A Bekkouche
Bulletin of the Seismological Society of America 102 (4), 1446-1461, 2012
1412012
Comparisons among the five ground-motion models developed using RESORCE for the prediction of response spectral accelerations due to earthquakes in Europe and the Middle East
J Douglas, S Akkar, G Ameri, PY Bard, D Bindi, JJ Bommer, SS Bora, ...
Bulletin of earthquake engineering 12, 341-358, 2014
962014
Site-condition proxies, ground motion variability, and data-driven GMPEs: Insights from the NGA-West2 and RESORCE data sets
B Derras, PY Bard, F Cotton
Earthquake spectra 32 (4), 2027-2056, 2016
802016
V S30, slope, H 800 and f 0: performance of various site-condition proxies in reducing ground-motion aleatory variability and …
B Derras, PY Bard, F Cotton
Earth, Planets and Space 69, 1-21, 2017
742017
Deriving amplification factors from simple site parameters using generalized regression neural networks: implications for relevant site proxies
A Boudghene Stambouli, D Zendagui, PY Bard, B Derras
Earth, Planets and Space 69, 1-26, 2017
462017
Ground Motion Prediction Model Using Adaptive Neuro-Fuzzy Inference Systems: An Example Based on the NGA-West 2 Data
M Ameur, B Derras, D Zendagui
Pure and Applied Geophysics 175 (3), 1019–1034, 2018
292018
Non-linear modulation of site response: Sensitivity to various surface ground-motion intensity measures and site-condition proxies using a neural network approach
B Derras, PY Bard, J Régnier, H Cadet
Engineering Geology, 2020
232020
Use of the artificial neural network for peak ground acceleration estimation
B Derras, A Bekkouche
Lebanese Science Journal 12 (2), 101-115, 2011
142011
An overview of the infrastructure seismic resilience assessment using Artificial Intelligence and Machine-learning algorithms
B Derras, N Makhoul
3rd International Conference on Natural Hazards & Infrastructure 5-7 July …, 2022
132022
Peak ground acceleration prediction using artificial neural networks approach: application to the Kik-Net data
B Derras
International Journal of Earthquake Engineering and Hazard Mitigation (IREHM …, 2014
12*2014
Neuronal approach and the use of kik-net network to generate response spectrum on the surface
B Derras, A Bekkouche, D Zendagui
Jordan Journal of Civil Engineering 4 (1), 2010
122010
2D/1D aggravation factors: from a comprehensive study to estimation with a neural network model
AB Stambouli, PY Bard, E Chaljub, P Moczo, J Kristek, S Stripajova, ...
16Ith European Conference of Earthquake Engineering, 2018
72018
Seismic resilience of interdependent built environment for integrating structural health monitoring and emerging technologies in decision-making
N Makhoul, M Roohi, JW van de Lindt, H Sousa, LO Santos, S Argyroudis, ...
Structural Engineering International 34 (1), 19-33, 2024
42024
Data-driven testing of the magnitude dependence of earthquake stress parameters using the NGA-West 2 dataset
Z Dif, B Derras, F Cotton, C Molkenthin
Journal of Seismology 24, 1095-1107, 2020
42020
Contribution des données accélérométriques de KiKNet à la prédiction du mouvement sismique par l'approche neuronale avec la prise en compte des effets de site
B Derras
Université de Tlemcen, 2011
42011
A regionalized partially nonergodic ground-motion data driven model for low to moderate seismicity areas: using RESIF-RAP, ESM, RESORCE and NGA-West2 data
F Chaibeddra Tani, B Derras
Bulletin of Earthquake Engineering 22 (4), 1677-1718, 2024
32024
MAGNITUDE DEPENDENCE OF STRESS DROP: WHAT DOES THE OBSERVED MAGNITUDE SCALING OF GROUND-MOTIONS TELL US?
B Derras, F Cotton, S Drouet, PY Bard
Sixteenth World Conference on Earthquake Engineering, 4505, 2017
32017
Artificial Intelligence for the amelioration of seismic resilience of bridges
B Derras, N Makhoul
IABSE Symposium Istanbul 2023: Long Span Bridges 191545, 277 - 284, 2023
22023
Prediction of recovery time of infrastructure functionalities after an earthquake using machine learning
B Derras, N Makhoul
Life-Cycle of Structures and Infrastructure Systems 1, 8, 2023
22023
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