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- W2045177655 abstract "A new self-adaptive improved differential evolution algorithm is presented. In order to improve the population's diversity and the ability of breaking away from the local optimum, according to the value of the variance of the population's fitness during the evolution process, a new mutation operator is adapted to mutate the population. In order to balance global and local search ability, the Scaling factor F is automatically updated according to the generations. In order to protect the better individuals to improve the convergent speed, the crossover rate CR is automatically updated according to the average value of the population's fitness. Several experimental results show that the new algorithm not only has can avoid the premature convergence remarkably, but also can improve convergent speed." @default.
- W2045177655 created "2016-06-24" @default.
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- W2045177655 date "2010-08-01" @default.
- W2045177655 modified "2023-10-18" @default.
- W2045177655 title "Self-adaptive improved differential evolution algorithm" @default.
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- W2045177655 doi "https://doi.org/10.1109/icnc.2010.5583486" @default.
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