Excellence in Research and Innovation for Humanity
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@article{(International Science Index):http://waset.org/publications/568,
  title    = {Neural Networks for Short Term Wind Speed Prediction},
  author    = {K. Sreelakshmi and  P. Ramakanthkumar},
  country   = {},
  abstract  = {Predicting short term wind speed is essential in order
to prevent systems in-action from the effects of strong winds. It also
helps in using wind energy as an alternative source of energy, mainly
for Electrical power generation. Wind speed prediction has
applications in Military and civilian fields for air traffic control,
rocket launch, ship navigation etc. The wind speed in near future
depends on the values of other meteorological variables, such as
atmospheric pressure, moisture content, humidity, rainfall etc. The
values of these parameters are obtained from a nearest weather
station and are used to train various forms of neural networks. The
trained model of neural networks is validated using a similar set of
data. The model is then used to predict the wind speed, using the
same meteorological information. This paper reports an Artificial
Neural Network model for short term wind speed prediction, which
uses back propagation algorithm.},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {2},
  number    = {6},
  year      = {2008},
  pages     = {2019 - 2023},
  ee        = {http://waset.org/publications/568},
  url       = {http://waset.org/Publications?p=18},
  bibsource = {http://waset.org/Publications},
  issn      = {PISSN:2010-376X, EISSN:2010-3778},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 18, 2008},