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Forecasting wind with neural networks

DSpace at IIT Bombay

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Field Value
 
Title Forecasting wind with neural networks
 
Creator MORE, ANURAG
DEO, MC
 
Subject coastal zones
wind turbines
recurrent neural networks
weather forecasting
 
Description Wind forecasts over a varying period of time are needed for a variety of applications in the coastal and ocean region, like planning of construction and operation-related works as well as prediction of power output from wind turbines located in coastal areas. Such forecasting is currently done by adopting complex atmospheric models or by using statistical time-series analysis. Because occurrence of wind in nature is extremely uncertain no single technique can be entirely satisfactory. This leaves scope for alternative approaches. The present work employs the technique of neural networks in order to forecast daily, weekly as well as monthly wind speeds at two coastal locations in India. Both feed forward as well as recurrent networks are used. They are trained based on past data in an auto-regressive manner using back-propagation and cascade correlation algorithms. A generally satisfactory forecasting as reflected in its higher correlation and lower deviations with actual observations is noted. The neural network forecasting is also found to be more accurate than traditional statistical time-series analysis.
 
Publisher Elsevier
 
Date 2009-03-23T05:10:52Z
2011-11-25T20:00:55Z
2011-12-26T13:07:58Z
2011-12-27T05:55:58Z
2009-03-23T05:10:52Z
2011-11-25T20:00:55Z
2011-12-26T13:07:58Z
2011-12-27T05:55:58Z
2003
 
Type Article
 
Identifier Marine Structures 16(1), 35-49
0951-8339
http://dx.doi.org/10.1016/S0951-8339(02)00053-9
http://hdl.handle.net/10054/1049
http://dspace.library.iitb.ac.in/xmlui/handle/10054/1049
 
Language en