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...
| 主要な著者: | , , , , , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English English |
| 出版事項: |
IEEE
2019
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| 主題: | |
| オンライン･アクセス: | 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 |