An application of Barnacle Mating Optimizer in Infectious Disease Prediction: A Dengue Outbreak Cases

Authors

  • Zuriani Mustaffa Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, 26300 Kuantan, Pahang, Malaysia
  • Mohd Herwan Sulaiman Faculty of Electrical & Electronics Engineering, Universiti Malaysia Pahang, 26600 Pekan, Pahang, Malaysia
  • Mohamad Farhan Mohamad Mohsin School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Yuhanis Yusof School of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
  • Ferda Ernawan Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, 26300 Kuantan, Pahang, Malaysia
  • Bariah Yusob Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, 26300 Kuantan, Pahang, Malaysia
  • Noorhuzaimi Mohd Noor Faculty of Computer Systems & Software Engineering, Universiti Malaysia Pahang, 26300 Kuantan, Pahang, Malaysia

DOI:

https://doi.org/10.24996/ijs.2020.61.8.28

Keywords:

Barnacles Mating Optimization, Dengue outbreak prediction, Meta-heuristic, Optimization, prediction

Abstract

Meta-heuristic algorithms have been significantly applied in addressing various real-world prediction problem, including in disease prediction. Having a reliable disease prediction model benefits many parties in providing proper preparation for prevention purposes. Hence, the number of cases can be reduced. In this study, a relatively new meta-heuristic algorithm namely Barnacle Mating Optimizer (BMO) is proposed for short term dengue outbreak prediction. The BMO prediction model is realized over real dengue cases data recorded in weekly frequency from Malaysia. In addition, meteorological data sets were also been employed as input. For evaluation purposes, error analysis relative to Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), and Mean Absolute Deviation (MAD) were employed to validate the performance of the identified algorithms which includes the comparison between BMO against Moth Flame Optimizer (MFO) and Grey Wolf Optimizer (GWO) algorithms. Upon simulation, the superiority is in favour to BMO by producing lower error rates.

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Published

2020-08-28

Issue

Section

Computer Science

How to Cite

An application of Barnacle Mating Optimizer in Infectious Disease Prediction: A Dengue Outbreak Cases. (2020). Iraqi Journal of Science, 61(8), 2132-2141. https://doi.org/10.24996/ijs.2020.61.8.28

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