Abstract
This article uses powerful technique of artificial neural network (ANN) models to simulate and estimate structural response of two-storey shear building by training the model for a particular earthquake. The neural network is first trained for a real earthquake data and the numerically generated responses of different floors of two-storey buildings as the training patterns. Trained ANN architecture is then used to simulate and test the structural response of different floors for various intensity earthquake data and it is found that the predicted responses given by ANN model are good for practical purposes. It is worth mentioning that although the simulation is done with numerically generated response data for particular earthquake, the idea may also be used for actual experimental (response) data.
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Acknowledgements
The authors would like to thank Seismology Division, Ministry of Earth Sciences, New Delhi, India for funding to carry out this investigation and the Dept. of Earthquake Eng., IIT, Roorkee for supplying some of the data. The author also wishes to thank the anonymous reviewers for valuable suggestions.
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Chakraverty, S., Gupta, P. & Sharma, S. Neural network-based simulation for response identification of two-storey shear building subject to earthquake motion. Neural Comput & Applic 19, 367–375 (2010). https://doi.org/10.1007/s00521-009-0279-6
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DOI: https://doi.org/10.1007/s00521-009-0279-6
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