Yadav, Pooja and Sagar, Atish (2019) Rainfall Prediction Using Artificial Neural Network (ANN) for tarai Region of Uttarakhand. Current Journal of Applied Science and Technology, 33 (5). pp. 1-7. ISSN 2457-1024
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Abstract
Rainfall prediction is clearly of great importance for any country. One would like to make long term prediction, i.e. predict total monsoon rainfall a few weeks or months and in advance short term prediction, i.e. predict rainfall over different locations a few days in advance [1]. Predicted by using its correlation with observed parameter. Several regression and neural network based models are currently available. While Artificial Neural Network provide a great deal of promise, they also embody much uncertainty [2,3]. In this paper, different artificial neural network models have been created for the rainfall prediction of Uttarakhand region in India. These ANN models were created using training algorithms namely, feed-forward back propagation algorithm [4,5]. The number of neurons for all the models was kept at 10. The mean squared error was measured for each model and the best accuracy was obtained by the feed-forward back propagation algorithm with MSE value as low as 0.00547823.
Item Type: | Article |
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Subjects: | STM Open Library > Multidisciplinary |
Depositing User: | Unnamed user with email support@stmopenlibrary.com |
Date Deposited: | 21 Apr 2023 05:42 |
Last Modified: | 25 Jul 2024 07:37 |
URI: | http://ebooks.netkumar1.in/id/eprint/1017 |