Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5474463 | Ocean Engineering | 2017 | 11 Pages |
Abstract
For the selection of the optimal model different architectures were studied, generating 50 models for each of them and selecting with better results and with the smaller number of neurons in the hidden layer. To evaluate the performance of the model, various statistical errors were used (absolute error, mean magnitude of relative error and percentage relative error), with an average absolute error of 17.3Â m in the distances to the coast and 0.26Â m in the depths. The results were compared with equations currently employed (Table 1), which show that the errors generated by the ANN (Artificial Neural Network) are much lower (per example the MAPE committed by the proposed equation for distance to shore of the crest is 47%, while the ANN is made of 29%).
Keywords
Related Topics
Physical Sciences and Engineering
Engineering
Ocean Engineering
Authors
Isabel López, Luis Aragonés, Yolanda Villacampa, José C. Serra,