Title : ( Crack Identification in Functionally Graded Beams Using Particle Swarm Optimization Algorithm and Artificial Neural Network )
Authors: Mohammad Hossein Abolbashari , Foad Nazari ,
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Abstract
In the first part of this paper, a cantilever beam is modeled using Finite Element Method (FEM) and its natural frequencies are obtained for different conditions of cracks. Then two Multi-Layer Feed Forward (MLFF) Artificial Neural Networks (ANNs) are designed for prediction of FGB\\\\\\\'s Cracks\\\\\\\' location and depth. Particle Swarm Optimization (PSO) and Back-Error Propagation (BEP) algorithms are applied for training ANNs. The accuracy of two training methods’ results is investigated.
Keywords
, Crack, Functionally graded beam, A neural network, Particle swarm optimization
@inproceedings{paperid:1026028,
author = {Abolbashari, Mohammad Hossein and Nazari, Foad},
title = {Crack Identification in Functionally Graded Beams Using Particle Swarm Optimization Algorithm and Artificial Neural Network},
booktitle = {21st International Conference on Mechanical Engineering, ISME2013},
year = {2013},
location = {تهران, IRAN},
keywords = {Crack; Functionally graded beam;A neural network; Particle swarm optimization},
}
%0 Conference Proceedings
%T Crack Identification in Functionally Graded Beams Using Particle Swarm Optimization Algorithm and Artificial Neural Network
%A Abolbashari, Mohammad Hossein
%A Nazari, Foad
%J 21st International Conference on Mechanical Engineering, ISME2013
%D 2013
