Forest fires are destroying wildlife habitat and pollutes air with emissions dangerous to human health. Increased carbon dioxide in the atmosphere by the wildfire contributes to the greenhouse effects and climate change. The ashes remove a lot of nutrients and eroded soils, causes landslides and flooding. Brunei Darussalam rich in biodiversity and tropical forest resources is increasingly recording more forest fires every year. These fires destroy the precious forest resources of the country, degrade the environmental quality particularly deteriorate air quality and cause significant economic loss in terms of property, infrastructure and possess threat to human health as well as ecosystem. Therefore, the objective of the study is to analyze the forest fire contributors such as topographic, human factor, climate, ignition factor, and vegetation and use a soft computing technique (machine learning) to classify the possible of occurrence.
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10 January 2023
8TH BRUNEI INTERNATIONAL CONFERENCE ON ENGINEERING AND TECHNOLOGY 2021
8–10 November 2021
Bandar Seri Begawan, Brunei Darussalam
Research Article|
January 10 2023
Soft computing techniques for prediction of forest fire occurrence in Brunei Darussalam
Muhammad Iskandar Hanafi Bin Pengiran Haji Zahari;
Muhammad Iskandar Hanafi Bin Pengiran Haji Zahari
1
Civil Engineering Programme Area, Faculty of Engineering, Universiti Teknologi Brunei
, Tungku Highway, Gadong, BE1410, Brunei Darussalam
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Rama Rao Karri;
Rama Rao Karri
a)
2
Petroleum and Chemical Engineering Programme Area, Faculty of Engineering, Universiti Teknologi Brunei
, Tungku Highway, Gadong, BE1410, Brunei Darussalam
a)Corresponding author: [email protected]
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Mohamed Hasnain Isa;
Mohamed Hasnain Isa
1
Civil Engineering Programme Area, Faculty of Engineering, Universiti Teknologi Brunei
, Tungku Highway, Gadong, BE1410, Brunei Darussalam
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El-Said Mamdouh Mahmoud Zahran;
El-Said Mamdouh Mahmoud Zahran
3
Department of Public Works, Faculty of Engineering, Ain Shams University
, Cairo 11517, Egypt
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S. M. Shiva Nagendra
S. M. Shiva Nagendra
4
Department of Civil Engineering, Indian Institute of Technology Madras
, Chennai India
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a)Corresponding author: [email protected]
AIP Conf. Proc. 2643, 030023 (2023)
Citation
Muhammad Iskandar Hanafi Bin Pengiran Haji Zahari, Rama Rao Karri, Mohamed Hasnain Isa, El-Said Mamdouh Mahmoud Zahran, S. M. Shiva Nagendra; Soft computing techniques for prediction of forest fire occurrence in Brunei Darussalam. AIP Conf. Proc. 10 January 2023; 2643 (1): 030023. https://doi.org/10.1063/5.0110349
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