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Artificial neural network prediction of bearing capacity of welded columns based on simplified welding simulations

机译:基于简化焊接模拟的焊接柱承载力人工神经网络预测

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This paper discusses the prediction of the bearing capacity of welded columns using artificial neural network. The built-up network is based on a finite amount of buckling load analyses using a simplified welding simulation approach to take into account directly the welding influence. The recent research showed that this approach combining simplified welding simulations and nonlinear buckling analysis can achieve a good balance between increased accuracy of the results and computational efficiency. In this study, a set of numerical results data will be analysed and used to train the optimized artificial neural network with the genetic algorithm and then the predicted results will be tested and verified. Finally, the potential and advantages of this new approach are discussed based on the error analysis.
机译:本文讨论了使用人工神经网络预测焊接柱的承载力。内置网络基于使用简化的焊接仿真方法直接考虑焊接影响的有限量的屈曲负荷分析。最近的研究表明,这种方法组合简化的焊接模拟和非线性屈曲分析可以在提高结果和计算效率之间实现良好的平衡。在该研究中,将分析一组数值术语数据,并用遗传算法训练优化的人工神经网络,然后将测试预测结果并验证。最后,基于误差分析讨论了这种新方法的潜在和优点。

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