Cahyadi, Tedy Agung and Jayadianti, Herlina and Amri, Nur Ali and Pitayandanu, Muhammad Fathurrahman and Ashar, Abu (2020) Monthly Prediction of Rainfall in Nickel Mine Area with Artificial Neural Network. -.
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Abstract
Rainfall prediction in the mining area was needed to assist the process of mine drainage, and monitoring the availability of water in the reservoir, which is a source of hydroelectric power. Various ANN architectures were examined in this study to make predictions with monthly rainfall parameters t-3, t-2 and t-1. It included supporting parameters such as average exposure time, humidity, temperature, wind speed, and finally predicts rainfall in the month of occurrence. The ANN architecture contains a hidden layer which was examined by the optimal number of neurons and epochs. Hidden neurons were tried from seven to fourteen. The results of experiment showed that the architecture [7-8-1, 500 epochs] concluded that ANN gave good resultts of MSE which were 0.05865 for training and 0.08725 for testing. Furthermore, the ANN algorithm has provided to predict rainfall with a good model
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > Q Science (General) |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
| Depositing User: | Dr. ST. MT Nur Ali Amri |
| Date Deposited: | 04 Apr 2021 05:17 |
| Last Modified: | 04 Apr 2021 05:17 |
| URI: | http://eprints.upnyk.ac.id/id/eprint/25045 |
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