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Assessment of RC exterior beam-column Joints based on artificial neural networks and other methods

机译:基于人工神经网络及其他方法的钢筋混凝土外梁柱节点评估

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A database on the behaviour of reinforced concrete external beam-column joint sub-assemblages established from the results of over 150 tests is developed and used for the development, training and validation of an artificial neural network (ANN) based model. The ANN model predictions on the mode of failure and load-carrying capacity of the joints, together with the predictions of widely used code methods and those of a recently proposed method, which does not require calibration through the use of test data, are compared with their counterparts stored in the database developed herein. The comparison confirms the already reported shortcomings of current code methods and demonstrates that both ANN model and the recently proposed method can provide reliable alternatives to the code methods. (C) 2017 Published by Elsevier Ltd.
机译:建立了基于150多个测试结果建立的钢筋混凝土外部梁-柱节点子组合行为的数据库,并将其用于基于人工神经网络(ANN)的模型的开发,训练和验证。将关节​​的失效模式和承载能力的ANN模型预测,以及广泛使用的编码方法和最近提出的方法(无需通过使用测试数据进行校准)的预测,与以下方法进行了比较:其对应物存储在此处开发的数据库中。比较结果证实了已经报道的当前编码方法的缺点,并证明了ANN模型和最近提出的方法都可以为编码方法提供可靠的替代方法。 (C)2017由Elsevier Ltd.发布

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