Sains Malaysiana 48(7)(2019): 1325–1332

http://dx.doi.org/10.17576/jsm-2019-4807-02

 

Artificial Intelligence Projection Model for Methane Emission from Livestock in Sarawak

(Unjuran Model Kecerdasan Buatan untuk Pelepasan Metana daripada Ternakan di Sarawak)

 

PENG ENG KIAT1*, MARLINDA ABDUL MALEK2 & SITI MARIYAM SHAMSUDDIN3

 

1Department of Civil Engineering, Universiti Tenaga Nasional, 43600 Kajang, Selangor Darul Ehsan, Malaysia

 

2Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional, 43600 Kajang, Selangor Darul Ehsan, Malaysia

 

3UTM Big Data Centre, Ibnu Sina Institute for Scientific and Industrial Research, Universiti Teknologi Malaysia, 81310 Johor Bahru, Johor Darul Takzim, Malaysia

 

Diserahkan: 2 Februari 2019/Diterima: 25 April 2019

 

ABSTRACT

Artificial Intelligence is a topical trend employed to solve engineering and industrial problems by virtue of its abilities to deal with data uncertainty such as methane emissions. Hard computing methods are not suitable for determining the optimal emission in a methane emission data set. Instead, soft computing solutions should be considered in an effort to obtain better optimal solutions for industrial problems. This paper utilized the Guidelines provided in the 2006 Intergovernmental Panel on Climate Change (IPCC) to calculate and project methane emissions from selected six livestock in Sarawak, Malaysia. A particle swarm optimization (PSO) model was developed to project future methane emission by using number of livestock as the input parameter. The total CH4 inventory from the enteric fermentation of cattle, buffaloes, goats, sheep, swine and deer in Sarawak decreased from 1.860 to 1.856 Gg when calculation was carried out using the Tier 1 method. This decrease was due to population growth and the emission factors employed. Three statistical measures, root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were employed for evaluation. PSO has been shown to be able to give an accurate projection. The results of this study provide a benchmark information which can be used by the Sarawak government to develop appropriate policies and mitigation strategies to reduce future carbon footprint in the Sarawak livestock sector.

 

Keywords: Enteric fermentation; livestock; manure management; methane inventory; Tier 1

 

ABSTRAK

Kecerdasan Buatan adalah tren topikal yang digunakan untuk menyelesaikan masalah kejuruteraan dan perindustrian berdasarkan kemampuannya untuk menangani ketidakpastian data seperti pelepasan metana. Kaedah pengkomputeran keras tidak sesuai untuk menentukan pelepasan optimum dalam set data pelepasan metana. Sebaliknya, penyelesaian pengkomputeran lembut perlu dipertimbangkan dalam usaha untuk mendapatkan penyelesaian optimum yang lebih baik untuk masalah perindustrian. Kertas ini menggunakan Garis Panduan yang disediakan dalam Panel Antara Kerajaan tentang Perubahan Cuaca (IPCC) 2006 untuk menghitung dan mengunjurkan pelepasan metana daripada enam jenis ternakan terpilih di Sarawak, Malaysia. Model Particle Swarm Optimization (PSO) telah dibangunkan untuk mengunjurkan pelepasan metana masa depan dengan menggunakan bilangan ternakan sebagai parameter input. Keseluruhan inventori CH4 daripada penternakan lembu, kerbau, kambing, biri-biri, khinzir dan rusa di Sarawak menurun daripada 1.860 hingga 1.856 Gg apabila pengiraan dilakukan menggunakan kaedah Tier 1. Penurunan ini disebabkan oleh pertumbuhan penduduk dan faktor pelepasan yang digunakan. Tiga langkah statistik, iaitu kesilapan akar min kesilapan (RMSE), bermakna ralat mutlak (MAE), dan kesilapan peratusan mutlak (MAPE) digunakan untuk penilaian. PSO telah terbukti dapat memberikan unjuran yang tepat. Hasil kajian ini memberikan maklumat penanda aras yang boleh digunakan oleh kerajaan Sarawak untuk membangunkan dasar dan strategi mitigasi yang sesuai untuk mengurangkan jejak karbon pada masa hadapan dalam sektor ternakan di Sarawak.

 

Kata kunci: Fermentasi enterik; inventori metana; pengurusan baja; ternakan; Tier 1

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*Pengarang untuk surat-menyurat; email: pengek@gmail.com

 

 

 

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