An oppositional learning prediction operator for simulated kalman filter

• Main Authors: Zuwairie, Ibrahim, Kamil Zakwan, Mohd Azmi, Badaruddin, Muhammad, Mohd Falfazli, Mat Jusof, Nor Azlina, Alias, Nor Hidayati, Abdul Aziz, Mohd Ibrahim, Shapiai
• Format: Conference or Workshop Item
• Language: English; English
• Published: 2018
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://umpir.ump.edu.my/id/eprint/22171/1/9.%20An%20Oppostional%20Learning%20Prediction%20Operator%20For%20Simulated%20Kalman%20Filter.pdf; http://umpir.ump.edu.my/id/eprint/22171/2/9.1%20An%20Oppostional%20Learning%20Prediction%20Operator%20For%20Simulated%20Kalman%20Filter.pdf; http://umpir.ump.edu.my/id/eprint/22171/

Simulated Kalman filter (SKF) is a recent metaheuristic optimization algorithm established in 2015. In the present study, we introduce a prediction operator in SKF to prolong its exploration and to avoid premature convergence. The proposed prediction operator is based on oppositional learning. The r...