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首页> 外文期刊>Structural Engineering and Mechanics >Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification
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Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Networks (ANNs) for structural damage identification

机译:自适应神经模糊推理系统(ANFIS)和人工神经网络(ANN)用于结构损伤识别

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摘要

In this paper, adaptive neuro-fuzzy inference system (ANFIS) and artificial neural networks (ANNs) techniques are developed and applied to identify damage in a model steel girder bridge using dynamic parameters. The required data in the form of natural frequencies are obtained from experimental modal analysis. A comparative study is made using the ANNs and ANFIS techniques and results showed that both ANFIS and ANN present good predictions. However the proposed ANFIS architecture using hybrid learning algorithm was found to perform better than the multilayer feedforward ANN which learns using the backpropagation algorithm. This paper also highlights the concept of ANNs and ANFIS followed by the detail presentation of the experimental modal analysis for natural frequencies extraction.
机译:本文开发了自适应神经模糊推理系统(ANFIS)和人工神经网络(ANN)技术,并利用动态参数将其用于识别模型钢梁桥中的损伤。固有频率形式的所需数据是从实验模态分析中获得的。使用人工神经网络和人工神经网络技术进行了比较研究,结果表明人工神经网络和人工神经网络都提供了良好的预测。然而,发现使用混合学习算法的拟议ANFIS体系结构比使用反向传播算法学习的多层前馈ANN的性能更好。本文还重点介绍了人工神经网络和ANFIS的概念,然后详细介绍了用于自然频率提取的实验模态分析。

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