The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Artificial Neural Network for Markov Chaining of Rainfall Over India
Abstract
Rainfall forecasting plays a significant role in water management for agriculture in a country like India where the economy depends heavily upon agriculture. In this paper, a feed forward artificial neural network (ANN) and a multiple linear regression model has been utilized for lagged time series data of monthly rainfall. The data for 23 years from 1990 to 2012 over Indian region has been used in this study. Convincing values of root mean squared error between actual monthly rainfall and that predicted by ANN has been found. It has been found that during monsoon months, rainfall of every n+3rd month can be predicted using last three months' (n, n+1, n+2) rainfall data with an excellent correlation coefficient that is more than 0.9 between actual and predicted rainfall. The probabilities of dry seasonal month, wet seasonal month for monsoon and non-monsoon months have been found.
Related Content
|
Dankan Gowda V., Anjali Sandeep Gaikwad, Pilli Lalitha Kumari, Erdal Buyukbicakci, Sengul Ibrahimoglu.
© 2025.
32 pages.
|
|
Debasish Banerjee, Ranjit Barua, Sudipto Datta, Dileep Pathote.
© 2025.
18 pages.
|
|
Kok Yeow You, Man Seng Sim.
© 2025.
96 pages.
|
|
Man Seng Sim, Kok Yeow You, Fahmiruddin Esa, Raimi Dewan, DiviyaDevi Paramasivam, Rozeha A. Rashid.
© 2025.
38 pages.
|
|
Mandeep Kaur.
© 2025.
24 pages.
|
|
Ganesh Khekare, Priya Dasarwar, Ajay Kumar Phulre, Urvashi Khekare, Gaurav Kumar Ameta, Shashi Kant Gupta.
© 2025.
22 pages.
|
|
Manoj Kumar Elipey, P. S. Kishore, Ratna Sunil Buradagunta.
© 2025.
14 pages.
|
|
|