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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
1352014
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
1242012
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
932014
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
752016
V S30, slope, H 800 and f 0: performance of various site-condition proxies in reducing ground-motion aleatory variability and predicting nonlinear site response
B Derras, PY Bard, F Cotton
Earth, Planets and Space 69 (1), 1-21, 2017
662017
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), 1-26, 2017
362017
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
252018
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
192020
Use of the artificial neural network for peak ground acceleration estimation
B Derras, A Bekkouche
Lebanese Science Journal 12 (2), 101-115, 2011
142011
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
112010
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
102022
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
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
32020
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
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
32011
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
Using ambient vibration measurements for risk assessment at an Urban scale: From numerical proof of concept to a case study in Beirut (Lebanon)
C Salameh, PY Bard, B Guillier, J Harb, C Cornou, M Almakari
IAEE International Symposium: Effects of Surface Geology on Seismic Motion …, 2016
22016
Estimation du risque lié à l’effet de site et génération d’un spectre de réponse à la surface libre
B DERRAS
22004
Testing the quality and performance of various proxies for ground-motion estimates in low-to-moderate seismicity areas: an example from RESIF data (mainland France)
B Derras, P-Y.Bard, E.Maufroy, C. Beauval, P.Traversa
17th World Conference on Earthquake Engineering, 12, 2021
1*2021
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