Evaluation of Different Horizon Lengths in Single-agent Finite Impulse Response Optimizer

Citation

Ab Aziz, Nor Azlina and Abdul Aziz, Nor Hidayati and Ibrahim, Zuwairie and Ab Rahman, Tasiransurini and Mohamad, Mohd Saberi and Shapiai, Mohd Ibrahim (2019) Evaluation of Different Horizon Lengths in Single-agent Finite Impulse Response Optimizer. In: 2019 International Conference on Computer and Information Sciences, ICCIS 2019, 3-4 April 2019, Sakaka, Saudi Arabia.

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Abstract

Single-agent Finite Impulse Response Optimizer (SAFIRO) is a newly single solution-based metaheuristic optimization algorithm which mimics the work procedure of the ultimate unbiased finite impulse response (UFIR) filter. In a real UFIR filter, the horizon length, N plays an important role to obtain the optimal estimation. In SAFIRO, N represents the repetition number of estimation part that needs to be done in finding an optimal solution. In the original SAFIRO, N = 4 is assigned. In this study, the effect of N towards the performance of SAFIRO is evaluated by assigning N between the range of 4 to 10. The CEC 2014 benchmark test suite is used for performance evaluations. Statistical analysis using the nonparametric Friedman test was performed to observe the performance. Experimental results show that N is a function dependent parameter where for certain functions, SAFIRO performs better with a larger value of N. However, for certain functions, SAFIRO performs better with a minimum value of N.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Estimation
Subjects: H Social Sciences > HA Statistics > HA1-4737 Statistics (General) > HA29-32 Theory and method of social science statistics
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 07 Jan 2022 03:35
Last Modified: 21 Dec 2022 06:20
URII: http://shdl.mmu.edu.my/id/eprint/8954

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