Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model

Green sea turtles, known scientifically as Chelonia mydas, prefer to nest on specific sandy beaches in Sarawak, particularly within the Sarawak Turtle Islands (STI). The number of turtles landing, among other variables (number of eggs collected, eggs incubated, and eggs hatched) is an important elem...

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Main Authors: Abang Mohammad Hudzaifah Abang Shakawi,, Ani Shabri,, Ruhana Hassan,
Format: Article
Language:English
Published: Penerbit Universiti Kebangsaan Malaysia 0002
Online Access:http://journalarticle.ukm.my/24759/1/MAE%2011.pdf
http://journalarticle.ukm.my/24759/
https://jms.mabjournal.com/index.php/mab/issue/view/63
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spelling my-ukm.journal.247592025-01-23T06:41:46Z http://journalarticle.ukm.my/24759/ Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model Abang Mohammad Hudzaifah Abang Shakawi, Ani Shabri, Ruhana Hassan, Green sea turtles, known scientifically as Chelonia mydas, prefer to nest on specific sandy beaches in Sarawak, particularly within the Sarawak Turtle Islands (STI). The number of turtles landing, among other variables (number of eggs collected, eggs incubated, and eggs hatched) is an important element in assessing the population size in Sarawak. However, modeling and predicting the number of turtles landing presents challenges due to limited data availability, resulting in less accurate forecasts for medium and long-term periods. To overcome this problem, this study presents a Grey Model (GM) approach, leveraging its capacity to effectively model systems with limited data, irregular patterns, and a lack of prior knowledge. Using data from 1949 to 2016, GM (1,1) was found to be the most suitable model for the given dataset, exhibiting the lowest Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) as compared to other statistical models such as Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM) and Exponential Smoothing. The model also suggested that the current conditions will likely increase turtle landings. This approach will find useful applications in evaluating the conservation status of the species. Penerbit Universiti Kebangsaan Malaysia 0002 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/24759/1/MAE%2011.pdf Abang Mohammad Hudzaifah Abang Shakawi, and Ani Shabri, and Ruhana Hassan, (0002) Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model. Malaysian Applied Biology, 53 (4). pp. 115-124. ISSN 0126-8643 https://jms.mabjournal.com/index.php/mab/issue/view/63
institution Universiti Kebangsaan Malaysia
building Tun Sri Lanang Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Kebangsaan Malaysia
content_source UKM Journal Article Repository
url_provider http://journalarticle.ukm.my/
language English
description Green sea turtles, known scientifically as Chelonia mydas, prefer to nest on specific sandy beaches in Sarawak, particularly within the Sarawak Turtle Islands (STI). The number of turtles landing, among other variables (number of eggs collected, eggs incubated, and eggs hatched) is an important element in assessing the population size in Sarawak. However, modeling and predicting the number of turtles landing presents challenges due to limited data availability, resulting in less accurate forecasts for medium and long-term periods. To overcome this problem, this study presents a Grey Model (GM) approach, leveraging its capacity to effectively model systems with limited data, irregular patterns, and a lack of prior knowledge. Using data from 1949 to 2016, GM (1,1) was found to be the most suitable model for the given dataset, exhibiting the lowest Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) as compared to other statistical models such as Autoregressive Integrated Moving Average (ARIMA), Long Short-Term Memory (LSTM) and Exponential Smoothing. The model also suggested that the current conditions will likely increase turtle landings. This approach will find useful applications in evaluating the conservation status of the species.
format Article
author Abang Mohammad Hudzaifah Abang Shakawi,
Ani Shabri,
Ruhana Hassan,
spellingShingle Abang Mohammad Hudzaifah Abang Shakawi,
Ani Shabri,
Ruhana Hassan,
Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model
author_facet Abang Mohammad Hudzaifah Abang Shakawi,
Ani Shabri,
Ruhana Hassan,
author_sort Abang Mohammad Hudzaifah Abang Shakawi,
title Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model
title_short Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model
title_full Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model
title_fullStr Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model
title_full_unstemmed Forecasting green sea turtle (Chelonia mydas) landing in Sarawak using grey model
title_sort forecasting green sea turtle (chelonia mydas) landing in sarawak using grey model
publisher Penerbit Universiti Kebangsaan Malaysia
publishDate 0002
url http://journalarticle.ukm.my/24759/1/MAE%2011.pdf
http://journalarticle.ukm.my/24759/
https://jms.mabjournal.com/index.php/mab/issue/view/63
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score 13.239859