Prediction of peatlands forest fires in Malaysia using machine learning
The occurrence of fires in tropical peatlands poses significant threats to their ecosystems. An Internet of Things (IoT) system was developed to measure and collect fire risk factors in the Raja Musa Forest Reserve (RMFR) in Selangor, Malaysia, to address this issue. In this paper, neural networks w...
| Main Authors: | , , , , |
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| Format: | Article |
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Multidisciplinary Digital Publishing Institute
2023
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| Online Access: | http://psasir.upm.edu.my/id/eprint/109439/ |
| _version_ | 1848865371570831360 |
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| author | Li, Lu Sali, Aduwati Noordin, Nor Kamariah Ismail, Alyani Hashim, Fazirulhisyam |
| author_facet | Li, Lu Sali, Aduwati Noordin, Nor Kamariah Ismail, Alyani Hashim, Fazirulhisyam |
| author_sort | Li, Lu |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | The occurrence of fires in tropical peatlands poses significant threats to their ecosystems. An Internet of Things (IoT) system was developed to measure and collect fire risk factors in the Raja Musa Forest Reserve (RMFR) in Selangor, Malaysia, to address this issue. In this paper, neural networks with different layers were employed to predict peatland forests’ Fire Weather Index (FWI). The neural network models used two sets of input parameters, consisting of four and nine fire factors. The predicted FWI values were compared with actual values obtained from the Malaysian meteorological department. The findings revealed that the five-layer neural network outperformed others in both the four-input and nine-input models. Specifically, the nine-input neural network achieved a mean square error (MSE) of 1.116 and a correlation of 0.890, surpassing the performance of the four-input neural network with the MSE of 1.537 and the correlation of 0.852. These results hold significant research and practical implications for precise peatland fire prevention, control, and the formulation of preventive measures. |
| first_indexed | 2025-11-15T14:03:39Z |
| format | Article |
| id | upm-109439 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T14:03:39Z |
| publishDate | 2023 |
| publisher | Multidisciplinary Digital Publishing Institute |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1094392024-08-05T02:15:55Z http://psasir.upm.edu.my/id/eprint/109439/ Prediction of peatlands forest fires in Malaysia using machine learning Li, Lu Sali, Aduwati Noordin, Nor Kamariah Ismail, Alyani Hashim, Fazirulhisyam The occurrence of fires in tropical peatlands poses significant threats to their ecosystems. An Internet of Things (IoT) system was developed to measure and collect fire risk factors in the Raja Musa Forest Reserve (RMFR) in Selangor, Malaysia, to address this issue. In this paper, neural networks with different layers were employed to predict peatland forests’ Fire Weather Index (FWI). The neural network models used two sets of input parameters, consisting of four and nine fire factors. The predicted FWI values were compared with actual values obtained from the Malaysian meteorological department. The findings revealed that the five-layer neural network outperformed others in both the four-input and nine-input models. Specifically, the nine-input neural network achieved a mean square error (MSE) of 1.116 and a correlation of 0.890, surpassing the performance of the four-input neural network with the MSE of 1.537 and the correlation of 0.852. These results hold significant research and practical implications for precise peatland fire prevention, control, and the formulation of preventive measures. Multidisciplinary Digital Publishing Institute 2023-07-18 Article PeerReviewed Li, Lu and Sali, Aduwati and Noordin, Nor Kamariah and Ismail, Alyani and Hashim, Fazirulhisyam (2023) Prediction of peatlands forest fires in Malaysia using machine learning. Forests, 14 (7). art. no. 1472. pp. 1-15. ISSN 1999-4907 https://www.mdpi.com/1999-4907/14/7/1472 10.3390/f14071472 |
| spellingShingle | Li, Lu Sali, Aduwati Noordin, Nor Kamariah Ismail, Alyani Hashim, Fazirulhisyam Prediction of peatlands forest fires in Malaysia using machine learning |
| title | Prediction of peatlands forest fires in Malaysia using machine learning |
| title_full | Prediction of peatlands forest fires in Malaysia using machine learning |
| title_fullStr | Prediction of peatlands forest fires in Malaysia using machine learning |
| title_full_unstemmed | Prediction of peatlands forest fires in Malaysia using machine learning |
| title_short | Prediction of peatlands forest fires in Malaysia using machine learning |
| title_sort | prediction of peatlands forest fires in malaysia using machine learning |
| url | http://psasir.upm.edu.my/id/eprint/109439/ http://psasir.upm.edu.my/id/eprint/109439/ http://psasir.upm.edu.my/id/eprint/109439/ |