Prediction model for occurrence of impact wave force |
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Authors: | Hajime Mase Toshikazu Kitano |
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Affiliation: | a Disaster Prevention Research Institute, Kyoto University, Gokasho, Uji 611, Japan;b Department of Civil Engineering, University of Tokushima, 2-1 Minami-Josanjima, Tokushima 770, Japan |
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Abstract: | This study investigates the applicability of neural networks to predict whether impact wave force will act on the upright section of a composite breakwater. We employ a three-layered neural network whose units of input layer are h/L, H/h, d/h and BM/h (h: the total water depth; L: the wavelength; H: the wave height; d: the water depth above the mound; BM: the horizontal distance from the shoulder of mound to the caisson). Teach signals are 0.99 and 0.01 according to the cases of occurrence and absence of impact wave force, respectively. The neural network whose parameters are determined through self-learning can accurately predict whether impact wave force occurs. |
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Keywords: | Neural network Impact wave force Wave pressure Composite breakwater |
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