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Paper Information

Journal:   JOURNAL OF THE PERSIAN GULF (MARINE SCIENCE)   DECEMBER 2013 , Volume 4 , Number 14; Page(s) 47 To 60.
 
Paper: 

APPLICATION OF ARTIFICIAL NEURAL NETWORK AND FUZZY INFERENCE SYSTEM IN PREDICTION OF BREAKING WAVE CHARACTERISTICS

 
 
Author(s):  DELAVARI EHSAN, MOSTAFA GHARABAGHI AHMAD REZA*, CHENAGHLOU MOHMMAD REZA
 
* FACULTY OF CIVIL ENGINEERING, SAHAND UNIVERSITY OF TECHNOLOGY, TABRIZ, IR IRAN
 
Abstract: 

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.

 
Keyword(s): WAVE BREAKING, BREAKER DEPTH AND HEIGHT, ARTIFICIAL NEURAL NETWORK, FUZZY INFERENCE SYSTEM, ANFIS
 
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