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- W2349056182 abstract "Aimed at the redundant and irrelevant features of flight data,a new feature selection method of flight data based on neural network is proposed.In order to overcome the disadvantages of traditional algorithms such as slow convergence and local minimum,the neural network is trained by an improving method synthesizing particle swarm optimization algorithm and Levenberg-Marquardt optimi-zation algorithm.When the neural network is trained well,feature importance of flight data is ranked using network weights,and then feature selection of flight data is carried out based on the rank of feature importance.The experimental results show that the new method remove redundant feature selection effectively,and improve the generalization ability of neural network as well." @default.
- W2349056182 created "2016-06-24" @default.
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- W2349056182 date "2007-01-01" @default.
- W2349056182 modified "2023-09-26" @default.
- W2349056182 title "Feature selection method of flight data based on neural network" @default.
- W2349056182 hasPublicationYear "2007" @default.
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