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Figure 21. Structure of ANN used <t>in</t> <t>MATLAB</t> (w = weight; b = bias).
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Figure 21. Structure of ANN used <t>in</t> <t>MATLAB</t> (w = weight; b = bias).
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Figure 21. Structure of ANN used <t>in</t> <t>MATLAB</t> (w = weight; b = bias).
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Figure 21. Structure of ANN used <t>in</t> <t>MATLAB</t> (w = weight; b = bias).
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Figure 21. Structure of ANN used <t>in</t> <t>MATLAB</t> (w = weight; b = bias).
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Figure 21. Structure of ANN used <t>in</t> <t>MATLAB</t> (w = weight; b = bias).
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Figure 21. Structure of ANN used in MATLAB (w = weight; b = bias).

Journal: Polymers

Article Title: Short-Beam Shear Strength of New-Generation Glass Fiber-Reinforced Polymer Bars Under Harsh Environment: Experimental Study and Artificial Neural Network Prediction Model.

doi: 10.3390/polym16233358

Figure Lengend Snippet: Figure 21. Structure of ANN used in MATLAB (w = weight; b = bias).

Article Snippet: In the final testing phase, a separate test subset is used to objecti l of t e fully trained model. For this study, the neural network toolbox in MATLAB (“nftool”) was employ d t develop a feed-forward back-propagation model using the Bay sian regularization algorithm.

Techniques: