An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer
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...
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my.ump.umpir.213762018-09-12T08:32:51Z http://umpir.ump.edu.my/id/eprint/21376/ An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer Nor Hidayati, Abdul Aziz Nor Azlina, Ab. Aziz Mohd Falfazli, Mat Jusof Saifudin, Razali Zuwairie, Ibrahim Asrul, Adam Mohd Ibrahim, Shapiai QA75 Electronic computers. Computer science 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. IEEE 2018 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21376/7/An%20Analysis%20on%20the%20Number%20of%20Agents%20Towards%20the%20Performance1.pdf Nor Hidayati, Abdul Aziz and Nor Azlina, Ab. Aziz and Mohd Falfazli, Mat Jusof and Saifudin, Razali and Zuwairie, Ibrahim and Asrul, Adam and Mohd Ibrahim, Shapiai (2018) 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 (ISMS2018), 8-10 May 2018 , Kuala Lumpur, Malaysia. pp. 16-21.. ISBN 978-1-5386-6539-8 |
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Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source |
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| language |
English |
| topic |
QA75 Electronic computers. Computer science |
| spellingShingle |
QA75 Electronic computers. Computer science Nor Hidayati, Abdul Aziz Nor Azlina, Ab. Aziz Mohd Falfazli, Mat Jusof Saifudin, Razali Zuwairie, Ibrahim Asrul, Adam Mohd Ibrahim, Shapiai An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer |
| description |
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. |
| format |
Conference or Workshop Item |
| author |
Nor Hidayati, Abdul Aziz Nor Azlina, Ab. Aziz Mohd Falfazli, Mat Jusof Saifudin, Razali Zuwairie, Ibrahim Asrul, Adam Mohd Ibrahim, Shapiai |
| author_facet |
Nor Hidayati, Abdul Aziz Nor Azlina, Ab. Aziz Mohd Falfazli, Mat Jusof Saifudin, Razali Zuwairie, Ibrahim Asrul, Adam Mohd Ibrahim, Shapiai |
| author_sort |
Nor Hidayati, Abdul Aziz |
| title |
An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer |
| title_short |
An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer |
| title_full |
An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer |
| title_fullStr |
An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer |
| title_full_unstemmed |
An Analysis on the Number of Agents Towards the Performance of the Simulated Kalman Filter Optimizer |
| title_sort |
analysis on the number of agents towards the performance of the simulated kalman filter optimizer |
| publisher |
IEEE |
| publishDate |
2018 |
| url |
http://umpir.ump.edu.my/id/eprint/21376/7/An%20Analysis%20on%20the%20Number%20of%20Agents%20Towards%20the%20Performance1.pdf http://umpir.ump.edu.my/id/eprint/21376/ |
| _version_ |
1822920194250506240 |
| score |
13.251652 |