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Interpolation of wave heights

DSpace at IIT Bombay

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Field Value
 
Title Interpolation of wave heights
 
Creator DEO, MC
KUMAR, NKIRAN
 
Subject correlation methods
mathematical models
remote sensing
neural networks
 
Description Remote sensing of waves often necessitates presentation of data in the form of wave height values grouped over large time intervals. This restricts their use to long-term applications only. This paper describes how such data can be made suitable for short-term usage in the field. Weekly mean significant wave heights were derived from their monthly mean observations with the help of different alternative techniques. These include model-free neural network schemes as well as model-based statistical and numerical methods. Superiority of neural networks was noted when the estimations were compared with corresponding observations. The network was trained using three different training algorithms, viz., error back propagation, conjugate gradient and cascade correlation. The technique of cascade correlation took minimum training time and showed better coefficient of correlation between observations and network output.
 
Publisher Elsevier
 
Date 2009-03-23T09:45:37Z
2011-11-25T20:20:58Z
2011-12-26T13:08:13Z
2011-12-27T05:56:13Z
2009-03-23T09:45:37Z
2011-11-25T20:20:58Z
2011-12-26T13:08:13Z
2011-12-27T05:56:13Z
2000
 
Type Article
 
Identifier Ocean Engineering 27(9), 907-919
0029-8018
http://dx.doi.org/10.1016/S0029-8018(99)00023-2
http://hdl.handle.net/10054/1089
http://dspace.library.iitb.ac.in/xmlui/handle/10054/1089
 
Language en