An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer

Citation

Abdul Aziz, Nor Hidayati and Ab Aziz, Nor Azlina and Mat Jusof, Mohd Falfazli and Razali, Saifudin and Ibrahim, Zuwairie and Adam, Asrul and Shapiai, Mohd Ibrahim (2019) An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer. In: 8th International Conference on Intelligent Systems, Modelling and Simulation, ISMS 2018, 8-10 May 2018, Kuala Lumpur, Malaysia.

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Abstract

This paper presents an analysis of simulated Kalman filter (SKF) optimization algorithm. The SKF algorithm is a population-based optimization algorithm and thus, requires the use of agents to perform a search process. In optimization, usually, different number of agent produces different performance in solving optimization problems. In this paper, the performance of SKF is investigated using different number of agent, from 10 up to 1000 agents. Using the same number of fitness evaluations, experimental results indicate that a surprisingly large population size offers higher performance in solving most optimization problems.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Simulated Kalman filter
Subjects: Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 04 Feb 2022 03:34
Last Modified: 21 Dec 2022 06:24
URII: http://shdl.mmu.edu.my/id/eprint/9060

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