| 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 | 155 | 2014 |
| 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 | 140 | 2012 |
| 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 | 96 | 2014 |
| 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 | 79 | 2016 |
| 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 | 74 | 2017 |
| 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 | 47 | 2017 |
| 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 | 28 | 2018 |
| 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 | 23 | 2020 |
| Use of the artificial neural network for peak ground acceleration estimation B Derras, A Bekkouche Lebanese Science Journal 12 (2), 101-115, 2011 | 14 | 2011 |
| 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 | 13 | 2022 |
| 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 | 13 | 2010 |
| 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 |
| 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 | 7 | 2018 |
| 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 | 4 | 2024 |
| 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 | 4 | 2020 |
| 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 | 4 | 2011 |
| 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 | 3 | 2024 |
| 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 | 3 | 2017 |
| 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 | 2 | 2023 |
| 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 | 2 | 2023 |
Pierre-Yves BardSenior scientist, ISTerreVerified email at univ-grenoble-alpes.fr
