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- W2389447768 abstract "PSO algorithm in an iterative process is easy to fall into local optimum,so that it is impossible to make the iteration realize the global optimum results.The convergence of PSO algorithm has been analyzed,and then we get the convergence domain of PSO with inertia weight.In the convergence domain,we select the commonly used learning factor to fix its value.Let the inertia weight decline and combine the average speed of update of the correction formula.Finally,we get the new improved particle swarm algorithm APSO.The algorithm can accelerate the convergence speed,improve accuracy and reduce the times of average iteration." @default.
- W2389447768 created "2016-06-24" @default.
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- W2389447768 date "2011-01-01" @default.
- W2389447768 modified "2023-09-25" @default.
- W2389447768 title "Improved PSO Algorithm Based on the Differential Ideas and Average Mechanism" @default.
- W2389447768 hasPublicationYear "2011" @default.
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