Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/4227
Title: Prediction of tides using hydrodynamic and neural network approaches
Authors: Vivekanandan, N.
Singh, C.B.
Keywords: Artificial neural network
back propagation
conservation of laws
hydrodynamic
tide
Issue Date: Mar-2003
Publisher: CSIR
Abstract: <smarttagtype namespaceuri="urn:schemas-microsoft-com:office:smarttags" name="PlaceType"><smarttagtype namespaceuri="urn:schemas-microsoft-com:office:smarttags" name="PlaceName"><smarttagtype namespaceuri="urn:schemas-microsoft-com:office:smarttags" name="place"> The Indian subcontinent with a long coastline distributed among nine coastal states and the islands group of Andaman-Nicobar and Lakshdeep Islands, requires prediction of tides at desired location, based on data from one place to another place, for planning and design needs, especially at interior of bays or at the vicinity of civil structures. There is no exact analytical model that can predict tides at desired locations, since the phenomenon involved is uncertain and random in nature. Artificial Neural Network (ANN) model provides a non-hydrodynamic mapping between given sets of input and output values. Built-in-dynamism in network tracing, data error tolerance and lack of requirements of any exogenous input, etc, make neural network modelling attractive. This paper reports a study to predict tides at Navalakhi station based on reference station at Okha of Gulf of Kutch. The paper also shows show that the ANN results of prediction of tides at Navalakhi could be encapsulated in hydrodynamic model so as to save enormous efforts involved in CPU time as well as long duration of boundary conditions at Okha to be prescribed. </smarttagtype></smarttagtype></smarttagtype>
Description: 25-30
URI: http://hdl.handle.net/123456789/4227
ISSN: 0379-5136
Appears in Collections:IJMS Vol.32(1) [March 2003]

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