Predict the Average Temperatures of Baghdad City by Used Artificial Neural Network
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 9
Abstract
This paper utilizes artificial neural networks (ANN) technique to improve temperature forecast performance of Baghdad city. Our study based on Feed Forward Backpropagation Artificial Neural Networks (BPANN) algorithm of which trained and tested by used a real world daily average temperatures of Bagdad city for ten years past for months of January and July. Aimed at providing forecasts in a schedule, for all Days of the month to help the meteorologist to foresee future weather temperature accurately and easily. Forecasts by ANN model has been compared with the actual results and the realistic output (with IMOS). The results has been Compared to the practical temperature prediction results, and shows that the BPANN forecasts have accuracy that gave reasonably very good result and can be considered as a good method for temperature predicting..
Authors and Affiliations
Hind Saleem Ibrahim Harba
Keywords
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- EP ID EP392112
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