Journal Title : International Journal of Modern Trends in Engineering and Science


Author’s Name : Hettal M Tokle | Jignesh A Joshiunnamed

Volume 03 Issue 12 2016

ISSN no:  2348-3121

Page no: 91-96

Abstract – Precipitation forecasting is used for multiple reasons in multiple areas like agriculture, energy supply, transportations, etc. Accuracy of precipitation conditions shown in forecast reports is very necessary. In this paper, the review was conducted to investigate a better approach for forecasting which compares many techniques such as Artificial Neural Network, Ensemble Neural Network, Back propagation Network, Radial Basis Function Network, General Regression Neural Network, Genetic Algorithm, Multilayer Perception, Fuzzy clustering, etc. which were used for different types of forecasting. Among which neural network with the back propagation algorithm performs prediction with minimal error, the model derived is run on that basis. Neural network is a complex network which is self-adaptive in nature. It learns by itself using the training data and generates some intelligent patterns which are useful for forecasting. This paper reviews various techniques and focuses mainly on neural network with back propagation technique for precipitation-forecasting. 

Keywords— Neural Network, Back propagation Algorithm, ANN, Precipitation Prediction, Multilayer Neural Network, Quantitative Forecast, rainfall forcast


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