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Ultimate Compressive Strength Prediction for Stiffened Panels by Counterpropagation Neural Networks (CPN) |
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| Authors: | WEI Dong and ZHANG Shengkun PhD Candidate School of Naval Architecture and Ocean Engineering Shanghai Jiao Tong University Shanghai P R China Professor School of Naval Architecture and Ocean Engineering Shanghai Jiao Tong University Shanghai P R China |
| Institution: | WEI Dong and ZHANG Shengkun Ph.D. Candidate,School of Naval Architecture and Ocean Engineering,Shanghai Jiao Tong University,Shanghai 200030,P. R. China Professor,School of Naval Architecture and Ocean Engineering,Shanghai Jiao Tong University,Shanghai 200030,P. R. China |
| Abstract: | Stiffened Panels are important strength members in ship and offshore structures, A new method based on counterpropagation neural networks (CPN) is proposed in this paper to predict the ultimate compres-sive strength of stiffened panels. Compared with two-parametric polynomial, this method can take more parameters into account and make more use of experimental data. Numerical study is carried out to verify the validation of this method. The new method may find wide application in practical design. |
| Keywords: | stiffened panels ultimate strength counterpropagation neural networks |
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