Simulated kalman filter algorithm with improved accuracy

• Main Authors: Mohd Falfazli, Mat Jusof, Ahmad Azwan, Abdul Razak, Shuhairie, Mohammad, Ahmad Nor Kasruddin, Nasir, Mohd Helmi, Suid, Mohd Ashraf, Ahmad, Zuwairie, Ibrahim
• Format: Book Section
• Language: English; English; English
• Published: Springer Singapore 2018
• Subjects: TK Electrical engineering. Electronics Nuclear engineering; TS Manufactures
• Online Access: http://umpir.ump.edu.my/id/eprint/22658/1/9.%20Simulated%20kalman%20filter%20algorithm%20with%20improved%20accuracy.pdf; http://umpir.ump.edu.my/id/eprint/22658/8/46.%20Simulated%20Kalman%20Filter%20algorithm%20with%20improved%20accuracy.pdf; http://umpir.ump.edu.my/id/eprint/22658/9/46.1%20Simulated%20Kalman%20Filter%20algorithm%20with%20improved%20accuracy.pdf; http://umpir.ump.edu.my/id/eprint/22658/; https://link.springer.com/chapter/10.1007/978-981-13-3708-6_29
• Institution: Universiti Malaysia Pahang

This paper presents an improved Simulated Kalman Filter optimiza-tion algorithm. It is a further enhancement of a Simulated Kalman Filter (SKF) optimization algorithm. SKF is a random based optimization algorithm inspired from Kalman Filter theory. An exponential term is introduced into Estimation stage of SKF to speed up the searching process and gain more chances in find-ing better solutions. Cost function value that represent an accuracy of a solution is considered as the ultimate goal. Every single agent carries an information about the accuracy of a solution in which will be used to compare with other so-lutions from other agents. A solution that has a lower cost function is consid-ered as the best solution. The algorithm is tested with various benchmark func-tions and compared with the original SKF algorithm. Result of the analysis on the accuracy tested on the benchmark functions shows that the proposed algo-rithm outperforms SKF significantly.