An Approach for Rainfall Prediction using Soft Computing

An Approach for Rainfall Prediction using Soft Computing

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2019 by IJETT Journal
Volume-67 Issue-3
Year of Publication : 2019
Authors : K C Gouda, Libujashree R, Priyanka Kumari, Manisha Sharma, Ambili D Nair
DOI :  10.14445/22315381/IJETT-V67I3P230

Citation 

MLA Style: K C Gouda, Libujashree R, Priyanka Kumari, Manisha Sharma, Ambili D Nair "An Approach for Rainfall Prediction using Soft Computing" International Journal of Engineering Trends and Technology 67.3 (2019): 158-164.

APA Style:K C Gouda, Libujashree R, Priyanka Kumari, Manisha Sharma, Ambili D Nair (2019). An Approach for Rainfall Prediction using Soft Computing. International Journal of Engineering Trends and Technology, 67(3), 158-164.

Abstract
Rainfallis an important weather parameter and it has direct impacts on different sectors like agriculture, health, water management etc. and also controls the economy of the country. Future predictions of rainfall in water-scarce region are highly important for effective water resource management particularly over country like India. An accurate rainfall forecasting is also very much needed for agriculture dependent countries like India. Statistical techniques for rainfall forecasting cannot perform accurately. Rainfall being highly non-linear and complicated phenomena it requires to use the state-of-the-artSoft computing techniques likeArtificial Neural Network (ANN) for the accurate and advanced forecasting of rainfall. In this work, the back-propagation algorithm is used to predict the rainfall over Bangalore city in India using the ANN in the super computer platform. The back-propagation model developed is trained and validated against actual rainfall of the region. Results showed that ANNs could perform well for predicting long-term the rainfall with acceptable accuracy.

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Keywords
Rainfall prediction, ANN, BPNN, data mining.