1. Neural network-based prediction of ground time history responses
- Author
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Ramdane Bahar, Ahmed Mebarki, Ismail Derbal, Nouredine Bourahla, Laboratoire de Modélisation et Simulation Multi Echelle (MSME), Centre National de la Recherche Scientifique (CNRS)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Université Paris-Est Marne-la-Vallée (UPEM), and Université Paris-Est Marne-la-Vallée (UPEM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Centre National de la Recherche Scientifique (CNRS)
- Subjects
Engineering ,Earthquake engineering ,Environmental Engineering ,Artificial neural network ,business.industry ,Computer Science::Neural and Evolutionary Computation ,0211 other engineering and technologies ,02 engineering and technology ,[SPI]Engineering Sciences [physics] ,Time history ,021105 building & construction ,[SPI.GCIV.RISQ]Engineering Sciences [physics]/Civil Engineering/Risques ,Earthquake shaking table ,Point (geometry) ,Artificial intelligence ,business ,ComputingMilieux_MISCELLANEOUS ,021101 geological & geomatics engineering ,Civil and Structural Engineering - Abstract
This article proposes a method based on artificial neural networks (ANN) to predict the time history responses at any point on the ground near a shaking table reaction mass (Earthquake Engineering ...
- Published
- 2017