Comparison of daily rainfall forecasting using multilayer perceptron neural network model
Rainfall is important in predicting weather forecast particularly to the agriculture sector and also in environment which gives great contribution towards the economy of the nation. Thus, it is important for the hydrologists to forecast daily rainfall in order to help the other people in the agricul...
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| Format: | Article |
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UAD INSTITUTE OF SCIENTIFIC PUBLICATION AND PRESS
2020
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| Online Access: | http://eprints.uthm.edu.my/6673/ |
| _version_ | 1848888878310621184 |
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| author | Masngut, Mazwin Arleena Ismail, Shuhaida Mustapha, Aida Mohd Yasin, Suhaila |
| author_facet | Masngut, Mazwin Arleena Ismail, Shuhaida Mustapha, Aida Mohd Yasin, Suhaila |
| author_sort | Masngut, Mazwin Arleena |
| building | UTHM Institutional Repository |
| collection | Online Access |
| description | Rainfall is important in predicting weather forecast particularly to the agriculture sector and also in environment which gives great contribution towards the economy of the nation. Thus, it is important for the hydrologists to forecast daily rainfall in order to help the other people in the agriculture sector to proceed with their harvesting schedules accordingly and to make sure the results of their crops would be satisfying. This study is set to forecast the daily rainfall future value using ARIMA model and Artificial Neural Network (ANN) model. Both method is evaluated by using Mean Absolute Error (MAE), Mean Forecast Error (MFE), Root Mean Squared Error (RMSE) and coefficient of determination (R ). The results showed that ANN model has outperformed results than ARIMA model. The results also showed ANN has under-forecast the daily rainfall data by 2.21% compare to ARIMA with over-forecast of -3.34%. From this study, it shows that the ANN (6,4,1) model produces better results of MAE (8.4208), MFE (2.2188), RMSE (34.6740) and R (0.9432) compared to ARIMA model. This has proved that ANN model has outperformed ARIMA model in predicting daily rainfall values. |
| first_indexed | 2025-11-15T20:17:17Z |
| format | Article |
| id | uthm-6673 |
| institution | Universiti Tun Hussein Onn Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T20:17:17Z |
| publishDate | 2020 |
| publisher | UAD INSTITUTE OF SCIENTIFIC PUBLICATION AND PRESS |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | uthm-66732022-03-14T01:50:54Z http://eprints.uthm.edu.my/6673/ Comparison of daily rainfall forecasting using multilayer perceptron neural network model Masngut, Mazwin Arleena Ismail, Shuhaida Mustapha, Aida Mohd Yasin, Suhaila QA299.6-433 Analysis Rainfall is important in predicting weather forecast particularly to the agriculture sector and also in environment which gives great contribution towards the economy of the nation. Thus, it is important for the hydrologists to forecast daily rainfall in order to help the other people in the agriculture sector to proceed with their harvesting schedules accordingly and to make sure the results of their crops would be satisfying. This study is set to forecast the daily rainfall future value using ARIMA model and Artificial Neural Network (ANN) model. Both method is evaluated by using Mean Absolute Error (MAE), Mean Forecast Error (MFE), Root Mean Squared Error (RMSE) and coefficient of determination (R ). The results showed that ANN model has outperformed results than ARIMA model. The results also showed ANN has under-forecast the daily rainfall data by 2.21% compare to ARIMA with over-forecast of -3.34%. From this study, it shows that the ANN (6,4,1) model produces better results of MAE (8.4208), MFE (2.2188), RMSE (34.6740) and R (0.9432) compared to ARIMA model. This has proved that ANN model has outperformed ARIMA model in predicting daily rainfall values. UAD INSTITUTE OF SCIENTIFIC PUBLICATION AND PRESS 2020 Article PeerReviewed Masngut, Mazwin Arleena and Ismail, Shuhaida and Mustapha, Aida and Mohd Yasin, Suhaila (2020) Comparison of daily rainfall forecasting using multilayer perceptron neural network model. IAES International Journal of Artificial Intelligence, 9 (3). pp. 456-463. ISSN 2252-8938 http://doi.org/10.11591/ijai.v9.i3.pp456-463 |
| spellingShingle | QA299.6-433 Analysis Masngut, Mazwin Arleena Ismail, Shuhaida Mustapha, Aida Mohd Yasin, Suhaila Comparison of daily rainfall forecasting using multilayer perceptron neural network model |
| title | Comparison of daily rainfall forecasting using multilayer perceptron neural network model |
| title_full | Comparison of daily rainfall forecasting using multilayer perceptron neural network model |
| title_fullStr | Comparison of daily rainfall forecasting using multilayer perceptron neural network model |
| title_full_unstemmed | Comparison of daily rainfall forecasting using multilayer perceptron neural network model |
| title_short | Comparison of daily rainfall forecasting using multilayer perceptron neural network model |
| title_sort | comparison of daily rainfall forecasting using multilayer perceptron neural network model |
| topic | QA299.6-433 Analysis |
| url | http://eprints.uthm.edu.my/6673/ http://eprints.uthm.edu.my/6673/ |