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Paper Title: An Artificial Recurrent Neural Network model for Weather Forecasting
Authors Name: M Swapna , N Sudhakar
Unique Id: IJSDR160723
Published In: Volume 1 Issue 9, September-2016
Abstract: Weather forecasting is an application of science and technology to predict the state of the atmosphere for a given location. The available NWP (numerical weather prediction) models do not generally provide forecasts with the accuracy at resolution appropriate for this task. This paper describes the precipitation of weather forecasting based on ANN. Weather forecasting is made by collecting quantitative data about the current atmosphere at a given place and using scientific understanding of atmospheric process to show the changes in the atmosphere. Artificial Neural network is the mimic of human ability which adapts the changing circumstances. It is a complex network with highly interconnected processing elements called Neurons. The Gradient Descent algorithm has been used to predict the visibility of Coastal Andhra Pradesh based on different parameters. The data of these parameters is normalized initially and then trained. Further the performance of network is compared and the weather parameter is predicted.
Keywords: Recurrent Artificial Neural Networks, Back propagation Algorithm, Gradient Descent strategy, Precipitation, Prediction
Cite Article: "An Artificial Recurrent Neural Network model for Weather Forecasting ", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 9, page no.43 - 47, September-2016, Available :http://www.ijsdr.org/papers/IJSDR160723.pdf
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Publication Details: Published Paper ID: IJSDR160723
Registration ID:160723
Published In: Volume 1 Issue 9, September-2016
DOI (Digital Object Identifier):
Page No: 43 - 47
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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