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Civil Engineering Infrastructures Journal، جلد ۴۷، شماره ۱، صفحات ۲۹-۴۲
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| عنوان انگلیسی |
Efficiency of Neural Networks for Estimating the Patch Load Resistance of Plate Girders with a Focus on Uncertainties in Material and Geometrical Properties |
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| چکیده انگلیسی مقاله |
In this paper, a sensitivity analysis of artificial neural networks (NNs) is presented and employed for estimating the patch load resistance of plate girders subjected to patch loading. To evaluate the accuracy of the proposed NN model, the results are compared with the previously proposed empirical models, so that we can estimate the resistance of plate girders subjected to patch loading. The empirical models are calibrated, for improving the formulae, with experimental data set which was collected from the corresponding literature. NNs models are later trained and validated through using the existing experimental data. In this process several NNs architectures are taken into account. A set of good NNs models are selected and then analyzed regarding their robustness when confronted with the test data set and regarding their ability to reproduce the effect of uncertainty on the data. A sensitivity analysis is conducted herein in order to investigate the effect of variability in material and geometrical properties of plate girders. Thereafter, several estimates measuring the efficiency and the quality of the NN model and the calibrated models are obtained and discussed. |
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| نویسندگان مقاله |
فرزاد شهابیان |
associate professor, civil engineering department, faculty of engineering, ferdowsi university of mashhad, mashhad, iran.
سازمان اصلی تایید شده: دانشگاه فردوسی (Ferdowsi university)
sidi محمد elachachi | sidi mohammed
professor, university of bordeaux1, i2m-gce, 33405 talence, france.
denys breysse |
professor, university of bordeaux1, i2m-gce, 33405 talence, france.
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| نشانی اینترنتی |
http://ceij.ut.ac.ir/article_50314_afd2c195149544066539f3c4860e2dc8.pdf |
| فایل مقاله |
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| زبان مقاله منتشر شده |
en |
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