Variability of wave-induced ripple migration in wave-flume experiments and its implications for sediment transport

16We integrate published data sets of field and laboratory experiments of wave 17 ripples and use genetic programming, a machine learning paradigm, in an attempt to 18 develop a universal equilibrium predictor for ripple wavelength, height, and steepness. 19We train our genetic programming algorithm with data selected using a maximum 20 dissimilarity selection routine. Thanks to this selection algorithm we use less data to train 21 the genetic programming software, allowing more data to be used as testing (i.e. to 22 compare our predictor vs. common prediction schemes). Our resulting predictor is 23 smooth and physically meaningful, different from other machine learning derived results. 24Furthermore our predictor incorporates wave orbital ripples that were previously 25 excluded from empirical prediction schemes, notably ripples in coarse sediment and long 26 wavelength, low height ripples ('hummocks'). This new predictor shows ripple length to 27 be a weakly nonlinear function of both bottom orbital excursion and grain size. Ripple 28 height and steepness are both nonlinear functions of grain size and predicted ripple length 29 (i.e. bottom orbital excursion and grain size). We test this new prediction scheme against 30 common (and recent) predictors and the new predictors yield a lower normalized root 31 mean squared error using the testing data. This study further demonstrates the 32 applicability of machine learning techniques to successfully develop well performing 33 predictors if data sets are large in size, extensive in scope, multidimensional, and 34 nonlinear. 35 36

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Predicting Wave-induced Ripple Geometry and Bottom Friction Factor

Xiao

et al. 2019

Journal of Coastal Research

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Variability of wave-induced ripple migration in wave-flume experiments and its implications for sediment transport

Cited by 5 publications

References 21 publications

An available formula of the sandy beach state induced by plunging waves

An available formula of the sandy beach state induced by plunging waves

Prediction of wave ripple characteristics using genetic programming

Predicting Wave-induced Ripple Geometry and Bottom Friction Factor

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