Abstract

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A RAINFALL PREDICTION MODEL USING ARTICIAL NEURAL NETWORK

Lubna Shaikh, Kirti Sawlani


Back propagation algorithm is most commonly used in neural network projects because it works faster than earlier approaches to learning and for its accuracy. Back propagation is a workhorse of learning in neural network.In back-propagation algorithm, there are two facets in its learning cycle, one to generate input pattern and another one to adjust the output by changing the weights of the network. There are many applications of feed forward neural network such as weather and financial predictions, face and signature detections etc. This paper describes the training, testing of data sets and finding the number of hidden neurons using back propagation algorithm for better performance. In the research, rainfall prediction in the region of Mumbai has been analyzed using feed forward network. In formulating artificial neural network based predictive models three layered network has been constructed. General terms: Rainfall, Prediction.