ANN Approach for Weather Prediction using Back Propagation
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2012 by IJETT Journal | ||
| Volume-3 Issue-1 |
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| Year of Publication : 2012 | ||
| Authors : Ch.Jyosthna Devi , B.Syam Prasad Reddy , K.Vagdhan Kumar ,B.Musala Reddy ,N.Raja Nayak |
Citation
Ch.Jyosthna Devi , B.Syam Prasad Reddy , K.Vagdhan Kumar ,B.Musala Reddy ,N.Raja Nayak. "ANN Approach for Weather Prediction using Back P ropagation". International Journal of Engineering Trends and Technology(IJETT). V3(1):19-23 Jan-Feb 2012. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
Temperature forecasting is important because they are used to protect life and property. Temperature for ecasting is the application of science and technology to predict the state of the temperature for a future time at a given location. Temperature for ecasts are made by collecting quantitative data about the current state of the atmosphere . A neural network can learn complex mappings from inputs to outputs, based solely on samples and require limited understanding from trainer, who can be guided by heuristics. In this paper , a neural network - based algorithm for predicting the temperature is presented .The Neural Networks packages upports different types of training or learning algorithms .One such algorithm is Back Propagati on Neural Network (BPN) technique. The main advantage of the BPN neural network method is that it can fairly approximate alarge class of functions . This method is more efficient than numerical differentiation. The simple meaning of this term is that our model has potential to capture the complex relationships between many factors that contribute to certain temperature. The proposed idea is tested using the real time data set. The results are compared with practical working of meteoro logical department and these results confirm that our model have the potential for successful application to temperature for ecasting.
References
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Keywords
FeedForwardNeuralNetwork,Temperature prediction,B a ck propagation,Training,ANN