:: Volume 4, Issue 14 (Winter 2013) ::
JPG 2013, 4(14): 47-60 Back to browse issues page
Application of Artificial Neural Network and Fuzzy Inference System in Prediction of Breaking Wave Characteristics
Ehsan Delavari *, Ahmad Reza Mostafa Gharabaghi, Mohmmad Reza Chenaghlou
Sahand University of Technology
Abstract:   (7884 Views)
Wave height as well as water depth at the breaking point are two basic parameters which are necessary for studying coastal processes. In this study, the application of soft computing-based methods such as artificial neural network (ANN), fuzzy inference system (FIS), adaptive neuro fuzzy inference system (ANFIS) and semi-empirical models for prediction of these parameters are investigated. The data sets used in this study are published laboratory and field data obtained from wave breaking on plane and barred, impermeable slopes collected from 24 sources. The comparison of results reveals that, the ANN model is more accurate in predicting both breaking wave height and water depth at the breaking point compared to the other methods.
Keywords: Wave breaking, Breaker depth and height, Artificial neural network, Fuzzy inference system, ANFIS.
Full-Text [PDF 1021 kb]   (2476 Downloads)    
Type of Study: Basic and Original Research | Subject: Marine Biology & Biotechnology
Received: 2014/05/10 | Accepted: 2014/05/10 | ePublished: 2014/05/10

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Volume 4, Issue 14 (Winter 2013) Back to browse issues page