期刊
APPLIED SCIENCES-BASEL
卷 6, 期 6, 页码 -出版社
MDPI
DOI: 10.3390/app6060164
关键词
armor stones; artificial neural network; harmony search algorithm; rubble mound structure; stability number
类别
资金
- National Research Foundation of Korea (NRF) - Ministry of Science, ICT and Future Planning [NRF-2014R1A2A2A01007921]
In this study, an artificial neural network (ANN) model is developed to predict the stability number of breakwater armor stones based on the experimental data reported by Van der Meer in 1988. The harmony search (HS) algorithm is used to determine the near-global optimal initial weights in the training of the model. The stratified sampling is used to sample the training data. A total of 25 HS-ANN hybrid models are tested with different combinations of HS algorithm parameters. The HS-ANN models are compared with the conventional ANN model, which uses a Monte Carlo simulation to determine the initial weights. Each model is run 50 times and the statistical analyses are conducted for the model results. The present models using stratified sampling are shown to be more accurate than those of previous studies. The statistical analyses for the model results show that the HS-ANN model with proper values of HS algorithm parameters can give much better and more stable prediction than the conventional ANN model.
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