Research Article Open Access

RBFNN Model for Predicting Nonlinear Response of Uniformly Loaded Paddle Cantilever

Abdullah H. Abdullah

Abstract

The Radial basis Function neural network (RBFNN) model has been developed for the prediction of nonlinear response for paddle Cantilever with built-in edges and different sizes, thickness and uniform loads. Learning data was performed by using a nonlinear finite element program, incremental stages of the nonlinear finite element analysis were generated by using 25 schemes of built paddle Cantilevers with different thickness and uniform distributed loads. The neural network model has 5 input nodes representing the uniform distributed load and paddle size, length, width and thickness, eight nodes at hidden layer and one output node representing the max. deflection response (1500×1 represent the deflection response of load). Regression analysis between finite element results and values predicted by the neural network model shows the least error.

American Journal of Applied Sciences
Volume 6 No. 1, 2009, 89-92

DOI: https://doi.org/10.3844/ajassp.2009.89.92

Submitted On: 8 May 2008 Published On: 31 January 2009

How to Cite: Abdullah, A. H. (2009). RBFNN Model for Predicting Nonlinear Response of Uniformly Loaded Paddle Cantilever . American Journal of Applied Sciences, 6(1), 89-92. https://doi.org/10.3844/ajassp.2009.89.92

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Keywords

  • RBFNN
  • cantilever
  • finite element
  • ANSYS