Oppositional learning prediction operator with jumping rate for simulated kalman filter

• Main Authors: Badaruddin, Muhammad, Mohd Saberi, Mohamad, Zuwairie, Ibrahim, Kamil Zakwan, Mohd Azmi, Mohd Ibrahim, Shapiai, Mohd Falfazli, Mat Jusof
• Format: Conference or Workshop Item
• Language: English; English
• Published: IEEE 2019
• Subjects: TK Electrical engineering. Electronics Nuclear engineering; TS Manufactures
• Online Access: http://umpir.ump.edu.my/id/eprint/25147/1/43.%20Oppositional%20learning%20prediction%20operator%20with%20jumping%20rate.pdf; http://umpir.ump.edu.my/id/eprint/25147/2/43.1%20Oppositional%20learning%20prediction%20operator%20with%20jumping%20rate.pdf; http://umpir.ump.edu.my/id/eprint/25147/; https://doi.org/10.1109/ICCISci.2019.8716382
• Institution: Universiti Malaysia Pahang

Simulated Kalman filter (SKF) is among the new generation of metaheuristic optimization algorithm established in 2015. In this 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 lea...