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Effective Compressive Strengths of Corner and Edge Concrete Columns Based on an Adaptive Neuro-Fuzzy Inference System

机译:基于自适应神经模糊推理系统的角拐角和边缘混凝土柱的有效抗压强度

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摘要

In the current design codes, the effective compressive strength can be used to reflect decrease in load-transfer performance when upper/lower columns and slabs have different concrete compressive strengths. In this regard, this study proposed a method that can accurately estimate the effective compressive strengths by using an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS is an algorithm that introduces a learning system that corrects errors into a fuzzy theory and has widely been used to solve problems with complex mechanisms. In order to constitute the ANFIS algorithm, 50 data randomly extracted from 75 existing test datasets were used in training, and 25 were used for verification. It was found that analysis using the ANFIS model provides a more accurate evaluation of the effective compressive strengths of corner and edge columns than do the equations specified in the current design codes. In addition, parametric studies were performed using the ANFIS model, and a simplified equation for calculating the effective compressive strength was proposed, so that it can be easily used in practice.
机译:在当前的设计代码中,当上/下塔和板坯具有不同的混凝土压缩强度时,有效的抗压强度可用于反映负载转移性能的降低。在这方面,该研究提出了一种方法,可以通过使用自适应神经模糊推理系统(ANFIS)来准确地估计有效压缩强度。 ANFIS是一种算法,它介绍了一种学习系统,可以纠正错误的模糊理论,并且广泛用于解决复杂机制的问题。为了构成ANFIS算法,在训练中使用从75个现有的测试数据集随机提取的50个数据,并且使用25个用于验证。发现使用ANFIS模型的分析提供了比当前设计代码中规定的方程更准确地评估角落和边缘列的有效压缩强度。另外,使用ANFIS模型进行参数研究,提出了一种用于计算有效抗压强度的简化方程,因此可以在实践中容易地使用。

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