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Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study

Forest fire causes major and expensive damage to a country, including ecological, economic and anthropological aspects. Still, there were a lot of uncertainties and knowledge regarding forest fire management, especially in small fire detection. Many past studies throughout the decades, in machine le...

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Main Authors: Noryanti, Muhammad, Amirah Hazwani, Roslin, Hanita, Daud, Kadir, Evizal Abdul, Maharani, Warih
Format: Conference or Workshop Item
Language:English
English
Published: AIP Publishing 2024
Subjects:
QA Mathematics
Online Access:http://umpir.ump.edu.my/id/eprint/42471/1/Predicting%20forest%20fire%20spots%20using%20nonparametric%20predictive%20inference%20with%20parametric%20copula%20-%20Malaysia%20case%20study.pdf
http://umpir.ump.edu.my/id/eprint/42471/2/Predicting%20forest%20fire%20spots%20using%20nonparametric%20predictive%20inference%20with%20parametric%20copula.pdf
http://umpir.ump.edu.my/id/eprint/42471/
https://doi.org/10.1063/5.0224342
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spelling my.ump.umpir.424712024-09-20T01:48:11Z http://umpir.ump.edu.my/id/eprint/42471/ Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study Noryanti, Muhammad Amirah Hazwani, Roslin Hanita, Daud Kadir, Evizal Abdul Maharani, Warih QA Mathematics Forest fire causes major and expensive damage to a country, including ecological, economic and anthropological aspects. Still, there were a lot of uncertainties and knowledge regarding forest fire management, especially in small fire detection. Many past studies throughout the decades, in machine learning approaches, were non-generalizable and needed more accuracy. Therefore, this study aims to introduce nonparametric predictive inference (NPI) with a parametric copula, which considers the dependence structure to predict the forest fire hotspots using the coordinate – longitude and latitude. The proposed method was theorized to perform better than the current models and be able to generalize in other regions with the same parameters. A case study of Malaysia was chosen as there was a lack of mathematical and statistical solutions in forest fire management in this country. The four copulae integrated with the proposed method generated imprecise probabilities with a minimal gap showing the forecasting accuracy. Amongst, Gumbel and Normal copula parameters displayed the best imprecise probabilities of forest fire occurrences for the Malaysia location due to the lowest differences. In conclusion, the NPI can be an alternative method to predict forest fire hotspots. AIP Publishing 2024 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/42471/1/Predicting%20forest%20fire%20spots%20using%20nonparametric%20predictive%20inference%20with%20parametric%20copula%20-%20Malaysia%20case%20study.pdf pdf en http://umpir.ump.edu.my/id/eprint/42471/2/Predicting%20forest%20fire%20spots%20using%20nonparametric%20predictive%20inference%20with%20parametric%20copula.pdf Noryanti, Muhammad and Amirah Hazwani, Roslin and Hanita, Daud and Kadir, Evizal Abdul and Maharani, Warih (2024) Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study. In: AIP Conference Proceedings. 30th National Symposium on Mathematical Sciences (SKSM30) , 26–27 September 2023 , Kedah, Malaysia. pp. 1-8., 3189 (1). ISBN 978-0-7354-5014-1 (Published) https://doi.org/10.1063/5.0224342
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA Mathematics
spellingShingle QA Mathematics
Noryanti, Muhammad
Amirah Hazwani, Roslin
Hanita, Daud
Kadir, Evizal Abdul
Maharani, Warih
Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study
description Forest fire causes major and expensive damage to a country, including ecological, economic and anthropological aspects. Still, there were a lot of uncertainties and knowledge regarding forest fire management, especially in small fire detection. Many past studies throughout the decades, in machine learning approaches, were non-generalizable and needed more accuracy. Therefore, this study aims to introduce nonparametric predictive inference (NPI) with a parametric copula, which considers the dependence structure to predict the forest fire hotspots using the coordinate – longitude and latitude. The proposed method was theorized to perform better than the current models and be able to generalize in other regions with the same parameters. A case study of Malaysia was chosen as there was a lack of mathematical and statistical solutions in forest fire management in this country. The four copulae integrated with the proposed method generated imprecise probabilities with a minimal gap showing the forecasting accuracy. Amongst, Gumbel and Normal copula parameters displayed the best imprecise probabilities of forest fire occurrences for the Malaysia location due to the lowest differences. In conclusion, the NPI can be an alternative method to predict forest fire hotspots.
format Conference or Workshop Item
author Noryanti, Muhammad
Amirah Hazwani, Roslin
Hanita, Daud
Kadir, Evizal Abdul
Maharani, Warih
author_facet Noryanti, Muhammad
Amirah Hazwani, Roslin
Hanita, Daud
Kadir, Evizal Abdul
Maharani, Warih
author_sort Noryanti, Muhammad
title Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study
title_short Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study
title_full Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study
title_fullStr Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study
title_full_unstemmed Predicting forest fire spots using nonparametric predictive inference with parametric copula: Malaysia case study
title_sort predicting forest fire spots using nonparametric predictive inference with parametric copula: malaysia case study
publisher AIP Publishing
publishDate 2024
url http://umpir.ump.edu.my/id/eprint/42471/1/Predicting%20forest%20fire%20spots%20using%20nonparametric%20predictive%20inference%20with%20parametric%20copula%20-%20Malaysia%20case%20study.pdf
http://umpir.ump.edu.my/id/eprint/42471/2/Predicting%20forest%20fire%20spots%20using%20nonparametric%20predictive%20inference%20with%20parametric%20copula.pdf
http://umpir.ump.edu.my/id/eprint/42471/
https://doi.org/10.1063/5.0224342
_version_ 1822924645738741760
score 13.23648

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