Badaruddin, Muhammad and Zuwairie, Ibrahim and Kamil Zakwan, Mohd Azmi and Khairul Hamimah, Abas and Nor Azlina, Ab. Aziz and Nor Hidayati, Abd Aziz and Mohd Saberi, Mohamad (2016) Performance Evaluation of Hybrid SKF Algorithms: Hybrid SKF-PSO and Hybrid SKF-GSA. In: National Conference For Postgraduate Research (NCON-PGR 2016) , 24-25 September 2016 , Universiti Malaysia Pahang, Pekan. pp. 865-874..
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Abstract
This paper presents a performance evaluation of hybrid Simulated Kalman Filter Gravitational Algorithm (SKF-GSA), and hybrid Simulated Kalman Filter Particle Swarm Optimization (SKF-PSO), for continuous numerical optimization problems. Simulated Kalman filter (SKF) was inspired by the estimation capability of Kalman filter. Every agent in SKF is regarded as a Kalman filter. The performance of the hybrid algorithms (SKF-GSA and SKF-PSO) is compared using CEC2014 benchmark dataset for continuous numerical optimization problems. Based on the analysis of experimental results, we found that the SKF-PSO performs the best among all.
| Item Type: | Conference or Workshop Item (Lecture) |
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| Uncontrolled Keywords: | Simulated Kalman Filter, Hybrid Simulated Kalman Filter, Continuous Numerical Optimization Problems |
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Faculty of Electrical & Electronic Engineering |
| Depositing User: | Rosfadilla Mohamad Zainun |
| Date Deposited: | 09 Dec 2016 05:59 |
| Last Modified: | 22 Aug 2017 07:09 |
| URI: | http://umpir.ump.edu.my/id/eprint/15724 |
| Download Statistic: | View Download Statistics |
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