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- W4285491129 abstract "The whale optimization algorithm (WOA) is a metaheuristic algorithm based on swarm intelligence and it mimics the hunting behavior of whales. It has the imperfection of premature convergence into local optima. In order to overcome this disadvantage, a multioperator WOA (MOWOA) is proposed. Four main strategies are introduced to the MOWOA to heighten the search capacity of WOA. The strategies include nonlinear adaptive parameter design, an exploration mechanism of honey badger, Cauchy factor strategy, and greedy strategy. This paper tests the versatility of MOWOA with three different types of benchmark functions, and a kind of seismic inversion problem are trialed run. From the experimental results, the performance of MOWOA outperforms the compared algorithms in global optimization." @default.
- W4285491129 created "2022-07-15" @default.
- W4285491129 creator A5057585043 @default.
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- W4285491129 date "2022-07-15" @default.
- W4285491129 modified "2023-09-26" @default.
- W4285491129 title "Seismic Inversion Problem Using a Multioperator Whale Optimization Algorithm" @default.
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- W4285491129 doi "https://doi.org/10.1155/2022/1966054" @default.
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