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- W2384497584 abstract "This paper analyzes binary PSO algorithm attribute and the reduction methods of attributes based on BPSO, proposes a binary particle swam optimization method based on simulated annealing. The simulated annealing is introduced when particles updated their position. The algorithm convergence is controlled by adjusting the speed of annealing. The particles would not easily jump out of the expected search area when the fall of temperature is slow enough, which improved the particles’ local search capability and made the optimization algorithm more efficient. This algorithm is applied to the attribute reduction of casing damage prediction attributes are reduced from original 62 to 12. The complexity of aftermath processing is significantly reduced." @default.
- W2384497584 created "2016-06-24" @default.
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- W2384497584 date "2009-01-01" @default.
- W2384497584 modified "2023-09-23" @default.
- W2384497584 title "Annealing selection strategy in attributes reduction based on BPSO" @default.
- W2384497584 hasPublicationYear "2009" @default.
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