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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2020)
[Effective from January 1, 2020]
For more details click here

ICV 2018: 95.39
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39
For more details click here

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PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2019.8(12): 1949-1963
DOI: https://doi.org/10.20546/ijcmas.2019.812.233


Daily Monsoon Rainfall Prediction using Artificial Neural Network (ANN) for Parbhani District of Maharashtra
Amit Rawat1, Pravendra Kumar2 and Vaibhav Deoli3*
1Department of Civil Engineering, Institute of Technology, Gopeshwar-246424, India
2Department of Soil and Water Conservation Engineering, GBPUA&T Pantnagar-263145, India
3Department of Civil Engineering, Inderprastha Engineering College, Sahibabad, Ghaziabad-201010, India
*Corresponding author
Abstract:

Rainfall is the most complex and difficult elements of hydrological cycle to understand and to model due to the complexity of atmospheric process. Long term prediction of rainfall is important for country like India where economy is mainly depends on agriculture. In the present study an attempt has been made to develop ANN models for prediction of daily rainfall for monsoon season at Parbhani District of Maharashtra, India. For the study, 30 years data (1985 to 2014) have been used. The 80% data (1985-2008) were used for model calibration and remaining 20% data (2008-2014) were used for validation. In the study, Gama test has been used to find best combination of input variables and after that back-propagation algorithm and tan sigmoid activation function were used to train and test the models. It was founded that the models are capable to predict the rainfall with adequate accuracy.


Keywords: Maharashtra, India, Monsoon season, Human culture, Hydrology
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How to cite this article:

Amit Rawat, Pravendra Kumar and Vaibhav Deoli. 2019. Daily Monsoon Rainfall Prediction using Artificial Neural Network (ANN) for Parbhani District of Maharashtra.Int.J.Curr.Microbiol.App.Sci. 8(12): 1949-1963. doi: https://doi.org/10.20546/ijcmas.2019.812.233