Record Details


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

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