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- W3089275871 abstract "This paper proposes a new modification and application of the Salp Swarm Algorithm (SSA). First, an improved Chaotic Salp Swarm Algorithm (CSSA) is proposed. The performance of the SSA algorithm is improved by introducing improvements such as Kent chaotic mapping. The proposed CSSA algorithm is applied to the parameter identification research of Multi-Input Multi-Output (MIMO) Hammerstein system with heavy-tail noise. Due to the existence of heavy-tail noise, the traditional identification method has failed. This paper uses the CSSA algorithm to transform the system identification problem into an optimization problem, which overcomes the impact of heavy-tail noise. Finally, simulation examples are used to verify the effectiveness of using CSSA algorithm to solve the identification problem of Hammerstein model." @default.
- W3089275871 created "2020-10-01" @default.
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- W3089275871 date "2020-08-01" @default.
- W3089275871 modified "2023-10-16" @default.
- W3089275871 title "Chaotic salp swarm algorithm: Application to parameter identification for MIMO Hammerstein model under heavy tail noise" @default.
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- W3089275871 doi "https://doi.org/10.1109/ihmsc49165.2020.00066" @default.
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