An Investigation of Artificial Neural Network Based Prediction Systems in Rain Forecasting

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Gopal Datt, Ashutosh Kumar Bhatt, Abhay Saxena

Abstract

The present research work is about to disaster mitigation using the applications of ANN. The ANN is used in the number of diverse fields due to its ability to model non linear patterns and self adjusting (learning) nature to produce consistent output when trained using supervised learning. This study utilizes Backpropagation Neural Network to train ANN models to mitigation of disaster through forecasting of Rainfall conditions of hilly areas of Uttarakhand (India). We used 12 learning algorithms of BPNN (as- traingd, traingdx, trainbfg, trainlm, etc.) to conduct 1296 models using supervised learning (MatLab command window) and the results are assessed using Mean Square Error (MSE).
DOI: 10.17762/ijritcc2321-8169.150853

Article Details

How to Cite
, G. D. A. K. B. A. S. “An Investigation of Artificial Neural Network Based Prediction Systems in Rain Forecasting”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 3, no. 8, Aug. 2015, pp. 5338-49, doi:10.17762/ijritcc.v3i8.4841.
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