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Neuro-fuzzy based approach for wave transmission prediction of horizontally interlaced multilayer moored floating pipe breakwater

DRS at CSIR-National Institute of Oceanography

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Title Neuro-fuzzy based approach for wave transmission prediction of horizontally interlaced multilayer moored floating pipe breakwater
 
Creator Patil, S.G.
Mandal, S.
Hegde, A.V.
Alavandar, S.
 
Subject wave transmission
Neuro-Fuzzy Inference System
floating breakwaters
 
Description The ocean wave system in nature is very complicated and physical model studies on floating breakwaters are expensive and time consuming. Till now, there has not been available a simple mathematical model to predict the wave transmission through floating breakwaters by considering all the boundary conditions. This is due to complexity and vagueness associated with many of the governing variables and their effects on the performance of breakwater. In the present paper, Adaptive Neuro-Fuzzy Inference System (ANFIS), an implementation of a representative fuzzy inference system using a back-propagation neural network like structure, with limited mathematical representation of the system, is developed. An ANFIS is trained on the data set obtained from experimental wave transmission of horizontally interlaced multilayer moored floating pipe breakwater using regular wave flume at Marine Structure Laboratory, National Institute of Technology Karnataka, Surathkal, India. Computer simulations conducted on this data shows the effectiveness of the approach in terms of statistical measures, such as correlation coefficient, root-mean-square error and scatter index. Influence of input parameters is assessed using the principal component analysis. Also results of ANFIS models are compared with that of artificial neural network models
 
Date 2011-01-14T10:41:54Z
2011-01-14T10:41:54Z
2011
 
Type Journal Article
 
Identifier Ocean Engineering, vol.38(1); 2011; 186-196
http://drs.nio.org/drs/handle/2264/3777
 
Language en
 
Rights An edited version of this paper was published by Elsevier. Copyright [2011] Elsevier
 
Publisher Elsevier