TY  - JOUR
T1  - Nonlinear Response of Uniformly Loaded Paddle Cantilever Based upon Intelligent Techniques
AU - , Akeel Ali Wannas AU - , Mohammed K. Abd 
JO  - Research Journal of Applied Sciences
VL  - 3
IS  - 8
SP  - 566
EP  - 571
PY  - 2008
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2008.566.571
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2008.566.571
KW  - SVM
KW  -nonlinear response
KW  -cantilever
KW  -finite element
KW  -uniformly loaded
KW  -sensors
AB  - Modeling and simulation are indispensable when dealing with complex engineering systems. It makes it possible to do essential assessment before systems are built, Cantilever, which can help to can alleviate the need for expensive experiments and it can provide support in all stages of a project from conceptual design, through commissioning and operation. This study deals with intelligent techniques modeling method for nonlinear response of uniformly loaded paddle. Two Intelligent techniques had been used (Redial Base Function Neural Network (RBFNN) and Support Vector Machine (SVM)). Firstly, the stress distributions and the vertical displacements of the designed cantilevers were simulated through (ANSYS) 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 Paddle Cantilever model has 2 NN; NN1 has 5 input nodes representing the uniform distributed load and paddle size, length, width and thickness, 8 nodes at hidden layer and one output node representing the maximum deflection response and NN2 has inputs nodes representing  maximum deflection and paddle size, length, width and thickness and one output representing sensitivity ( R/R). The result shows that of the nonlinear response based upon SVM modeling better than RBFNN on basis of time, accuracy and robustness, particularly when both has same input and output data.
ER  -