Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam

Muhammad Iskandar Hanafi Bin Pengiran Haji Zahari; Rama Rao Karri; Mohamed Hasnain Isa; El Said Mamdouh Mahmoud Zahran; S. M. Shiva Nagendra

doi:10.1063/5.0110349

Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam

Muhammad Iskandar Hanafi Bin Pengiran Haji Zahari
, Rama Rao Karri^*
, Mohamed Hasnain Isa
, El Said Mamdouh Mahmoud Zahran
, S. M. Shiva Nagendra

^*Corresponding author for this work

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	8th Brunei International Conference on Engineering and Technology 2021
Editors	Mohammad Yeakub Ali, Rama Rao Karri, Shahriar Shams, Roslynna Rosli, Ena Kartina Abdul Rahman, Ramesh Singh
Publisher	American Institute of Physics Inc.
ISBN (Electronic)	9780735442795
DOIs	https://doi.org/10.1063/5.0110349
Publication status	Published - 10 Jan 2023
Externally published	Yes
Event	8th Brunei International Conference on Engineering and Technology 2021, BICET 2021 - Bandar Seri Begawan, Brunei Darussalam Duration: 8 Nov 2021 → 10 Nov 2021

Publication series

Name	AIP Conference Proceedings
Volume	2643
ISSN (Print)	0094-243X
ISSN (Electronic)	1551-7616

Conference

Conference	8th Brunei International Conference on Engineering and Technology 2021, BICET 2021
Country/Territory	Brunei Darussalam
City	Bandar Seri Begawan
Period	8/11/21 → 10/11/21

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 8 Decent Work and Economic Growth
SDG 11 Sustainable Cities and Communities
SDG 13 Climate Action

Free Keywords

artificial neural network
contributing factors
Forest fires
soft computing techniques
support vector machine

ASJC Scopus subject areas

General Physics and Astronomy

Access to Document

10.1063/5.0110349

Cite this

Zahari, M. I. H. B. P. H., Karri, R. R., Isa, M. H., Mahmoud Zahran, E. S. M., & Shiva Nagendra, S. M. (2023). Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam. In M. Y. Ali, R. R. Karri, S. Shams, R. Rosli, E. K. A. Rahman, & R. Singh (Eds.), 8th Brunei International Conference on Engineering and Technology 2021 Article 030023 (AIP Conference Proceedings; Vol. 2643). American Institute of Physics Inc.. https://doi.org/10.1063/5.0110349

Zahari, Muhammad Iskandar Hanafi Bin Pengiran Haji ; Karri, Rama Rao ; Isa, Mohamed Hasnain et al. / Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam. 8th Brunei International Conference on Engineering and Technology 2021. editor / Mohammad Yeakub Ali ; Rama Rao Karri ; Shahriar Shams ; Roslynna Rosli ; Ena Kartina Abdul Rahman ; Ramesh Singh. American Institute of Physics Inc., 2023. (AIP Conference Proceedings).

@inproceedings{724082a2ecd24d058ecdc916aa33717a,

title = "Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam",

abstract = "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.",

keywords = "artificial neural network, contributing factors, Forest fires, soft computing techniques, support vector machine",

author = "Zahari, \{Muhammad Iskandar Hanafi Bin Pengiran Haji\} and Karri, \{Rama Rao\} and Isa, \{Mohamed Hasnain\} and \{Mahmoud Zahran\}, \{El Said Mamdouh\} and \{Shiva Nagendra\}, \{S. M.\}",

note = "Publisher Copyright: {\textcopyright} 2023 American Institute of Physics Inc.. All rights reserved.; 8th Brunei International Conference on Engineering and Technology 2021, BICET 2021 ; Conference date: 08-11-2021 Through 10-11-2021",

year = "2023",

month = jan,

day = "10",

doi = "10.1063/5.0110349",

language = "English",

series = "AIP Conference Proceedings",

publisher = "American Institute of Physics Inc.",

editor = "Ali, \{Mohammad Yeakub\} and Karri, \{Rama Rao\} and Shahriar Shams and Roslynna Rosli and Rahman, \{Ena Kartina Abdul\} and Ramesh Singh",

booktitle = "8th Brunei International Conference on Engineering and Technology 2021",

}

Zahari, MIHBPH, Karri, RR, Isa, MH, Mahmoud Zahran, ESM & Shiva Nagendra, SM 2023, Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam. in MY Ali, RR Karri, S Shams, R Rosli, EKA Rahman & R Singh (eds), 8th Brunei International Conference on Engineering and Technology 2021., 030023, AIP Conference Proceedings, vol. 2643, American Institute of Physics Inc., 8th Brunei International Conference on Engineering and Technology 2021, BICET 2021, Bandar Seri Begawan, Brunei Darussalam, 8/11/21. https://doi.org/10.1063/5.0110349

Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam. / Zahari, Muhammad Iskandar Hanafi Bin Pengiran Haji; Karri, Rama Rao; Isa, Mohamed Hasnain et al.
8th Brunei International Conference on Engineering and Technology 2021. ed. / Mohammad Yeakub Ali; Rama Rao Karri; Shahriar Shams; Roslynna Rosli; Ena Kartina Abdul Rahman; Ramesh Singh. American Institute of Physics Inc., 2023. 030023 (AIP Conference Proceedings; Vol. 2643).

Research output: Chapter in Book/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam

AU - Zahari, Muhammad Iskandar Hanafi Bin Pengiran Haji

AU - Karri, Rama Rao

AU - Isa, Mohamed Hasnain

AU - Mahmoud Zahran, El Said Mamdouh

AU - Shiva Nagendra, S. M.

PY - 2023/1/10

Y1 - 2023/1/10

N2 - 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.

AB - 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.

KW - artificial neural network

KW - contributing factors

KW - Forest fires

KW - soft computing techniques

KW - support vector machine

UR - https://www.scopus.com/pages/publications/85146530501

U2 - 10.1063/5.0110349

DO - 10.1063/5.0110349

M3 - Conference contribution

AN - SCOPUS:85146530501

T3 - AIP Conference Proceedings

BT - 8th Brunei International Conference on Engineering and Technology 2021

A2 - Ali, Mohammad Yeakub

A2 - Karri, Rama Rao

A2 - Shams, Shahriar

A2 - Rosli, Roslynna

A2 - Rahman, Ena Kartina Abdul

A2 - Singh, Ramesh

PB - American Institute of Physics Inc.

T2 - 8th Brunei International Conference on Engineering and Technology 2021, BICET 2021

Y2 - 8 November 2021 through 10 November 2021

ER -

Zahari MIHBPH, Karri RR, Isa MH, Mahmoud Zahran ESM, Shiva Nagendra SM. Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam. In Ali MY, Karri RR, Shams S, Rosli R, Rahman EKA, Singh R, editors, 8th Brunei International Conference on Engineering and Technology 2021. American Institute of Physics Inc. 2023. 030023. (AIP Conference Proceedings). doi: 10.1063/5.0110349

Soft Computing Techniques for Prediction of Forest Fire Occurrence in Brunei Darussalam

Abstract

Publication series

Conference

UN SDGs

Free Keywords

ASJC Scopus subject areas

Access to Document

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