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- W4384026390 abstract "To optimize the furnace temperature prediction model for an aluminum melting process, an improved sand cat swarm optimization (PSCSO) is proposed. Firstly, a chaotic convergence factor is introduced in the process of each iteration, which changes the strategy selection mechanism of the algorithm and improves its speed and accuracy. Secondly, a population redistribution strategy is designed at the completion of each iteration to increase the algorithm's space utilization of the solution space. Finally, an optimal value jumping strategy is proposed to avoid the algorithm from falling into local optimum at the later stage of iteration. The proposed method is validated on some common benchmark functions and an example of its application used in aluminum smelting. The results show that PSCSO has better performance compared with other optimization algorithms." @default.
- W4384026390 created "2023-07-13" @default.
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- W4384026390 date "2023-05-19" @default.
- W4384026390 modified "2023-09-23" @default.
- W4384026390 title "An Improved Sand Cat Swarm Optimization and Its Application in Aluminum Melting Process" @default.
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- W4384026390 doi "https://doi.org/10.1109/icmsp58539.2023.10171007" @default.
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