Oppositional learning prediction operator with jumping rate for simulated kalman filter

Oppositional learning prediction operator with jumping rate for simulated kalman filter

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...

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Bibliográfalaš dieđut
Váldodahkkit: Badaruddin, Muhammad, Mohd Saberi, Mohamad, Zuwairie, Ibrahim, Kamil Zakwan, Mohd Azmi, Mohd Ibrahim, Shapiai, Mohd Falfazli, Mat Jusof
Materiálatiipa: Conference or Workshop Item
Giella:English
English
Almmustuhtton: IEEE 2019
Fáttát:
TK Electrical engineering. Electronics Nuclear engineering
TS Manufactures
Liŋkkat: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

Interneahtta

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

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