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Structural Engineering and Mechanics Volume 71, Number 6, September25 2019 , pages 739-749 DOI: https://doi.org/10.12989/sem.2019.71.6.739 |
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Reliability analysis of simply supported beam using GRNN, ELM and GPR |
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Jagan J, Pijush Samui and Dookie Kim
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| Abstract | ||
| This article deals with the application of reliability analysis for determining the safety of simply supported beam under the uniformly distributed load. The uncertainties of the existing methods were taken into account and hence reliability analysis has been adopted. To accomplish this aim, Generalized Regression Neural Network (GRNN), Extreme Learning Machine (ELM) and Gaussian Process Regression (GPR) models are developed. Reliability analysis is the probabilistic style to determine the possibility of failure free operation of a structure. The application of probabilistic mathematics into the quantitative aspects of a structure and improve the qualitative aspects of a structure. In order to construct the GRNN, ELM and GPR models, the dataset contains Modulus of Elasticity (E), Load intensity (w) and performance function () in which E and w are inputs and is the output. The achievement of the developed models was weighed by various statistical parameters; one among the most primitive parameter is Coefficient of Determination (R2) which has 0.998 for training and 0.989 for testing. The GRNN outperforms the other ELM and GPR models. Other different statistical computations have been carried out, which speaks out the errors and prediction performance in order to justify the capability of the developed models. | ||
| Key Words | ||
| beam; deflection; ELM; GPR; GRNN; prediction | ||
| Address | ||
| Jagan J:1School of Civil Engineering, Galgotias University, Greater Noida, Uttar Pradesh-201 308, India Pijush Samui: Department of Civil Engineering, National Institute of Technology Patna, Patna, Bihar, India Dookie Kim: Department of Civil Engineering, Kunsan National University, Kunsan, Jeonbuk, South Korea | ||