• Sudipti Banerjee
• Amit Kumar Manjhvar

Rainfall prediction aims to determine rainfall over a particular location. It is important for agriculture and other industry as well as the economy of the country. Accuracy in prediction could decrease the number of fatalities. Correct and in time information about rainfall can be helpful to take a decision on an on-going construction project, transportation business, flight navigation, etc. In the current work, a Hybrid Neural Network (HNN) model is proposed for the prediction of rainfall. HNN model gains the accuracy of 93.74%. The dataset used in this work is of Gwalior region over the period from 1990 to 2018.

Rainfall Prediction, Artificial Neural Network (ANN), Clustering, Classification, Expert Models, Levenberg-Marquardt Backpropagation, sequentialfs.

"Rainfall Prediction for Socio - Economic Benefits using Machine Learning over Gird Region of India.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.468-474, June-2019, Available :http://www.jetir.org/papers/JETIR1906B75.pdf

"Rainfall Prediction for Socio - Economic Benefits using Machine Learning over Gird Region of India.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp468-474, June-2019, Available at : http://www.jetir.org/papers/JETIR1906B75.pdf