Rainfall Forecasting Using Backpropagation Neural Network

Main Authors: Sihananto, Andreas Nugroho, Mahmudy, Wayan Firdaus
Format: Article info application/pdf Journal
Bahasa: eng
Terbitan: Faculty of Computer Science (FILKOM) Brawijaya University , 2017
Online Access: http://jitecs.ub.ac.id/index.php/jitecs/article/view/9
http://jitecs.ub.ac.id/index.php/jitecs/article/view/9/18
Daftar Isi:
  • Rainfall already became vital observation object because it affects society life both in rural areas or urban areas. Because parameters to predict rainfall rates is very complex, using physics based model that need many parameters is not a good choice. Using alternative approach like time-series based model is a good alternative. One of the algorithm that widely used to predict future events is Neural Network Backpropagation. On this research we will use Nguyen-Widrow method to initialize weight of Neural Network to reduce training time. The lowest MSE achieved is {0,02815; 0,01686; 0,01934; 0,03196} by using 50 maximum epoch and 3 neurons on hidden layer.