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Free vibration analysis of elastically supported Timoshenko columns with attached masses using fuzzy neural network

机译:用模糊神经网络分析弹性支承的蒂莫申科圆柱体的自由振动

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摘要

This study presents elastically supported Timoshenko column with attached masses for free vibration analysis using fuzzy neural network. Neuro fuzzy frequency estimation (NFEE) models were developed to compute vibration frequencies using fuzzy logic toolbox of software Matlab 7.0. Gaussian membership functions and adaptive neuro fuzzy inference system (ANFIS) were used in NFFE model. Hybrid learning rule was applied for quantifying output variables in NFFE model. Frequency values of column with 1, 5 and 10 attached masses were computed. Training sets for NFFE models used transfer matrix method (TMM). During testing of NFFE model, good agreement was observed with results obtained using TMM as reduction in computation effort.
机译:这项研究提出了带有附加质量的弹性支撑Timoshenko柱,用于使用模糊神经网络进行自由振动分析。使用软件Matlab 7.0的模糊逻辑工具箱,开发了神经模糊频率估计(NFEE)模型来计算振动频率。在NFFE模型中使用了高斯隶属函数和自适应神经模糊推理系统(ANFIS)。混合学习规则被用于量化NFFE模型中的输出变量。计算具有1、5和10个附着质量的色谱柱的频率值。 NFFE模型的训练集使用传递矩阵法(TMM)。在NFFE模型测试期间,观察到与使用TMM获得的结果一致,从而减少了计算工作量。

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