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• W2059135848 abstract "In this paper, a new hybrid learning algorithm based on the global optimization techniques, is introduced to evolve the Flexible Beta Basis Function Neural Tree (FBBFNT). The structure is developed using the Extended Immune Programming (EIP) and the Beta parameters and connected weights are optimized using the Opposite-based Particle Swarm Optimization (OPSO) algorithm. The performance of the proposed method is evaluated for time series prediction area and is compared with those of associated methods." @default.
• W2059135848 created "2016-06-24" @default.
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• W2059135848 date "2013-06-01" @default.
• W2059135848 modified "2023-10-14" @default.
• W2059135848 title "Extended immune programming and opposite-based PSO for evolving flexible beta basis function neural tree" @default.
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• W2059135848 doi "https://doi.org/10.1109/cybconf.2013.6617425" @default.
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