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- W2393083508 abstract "A large number of properties need to be selected into the appropriate attributes sets to describe the manufacturing system state in order to reduce the redundancy of attributes and reduce the computational complexity.A feature selection method was proposed based on immune binary partial swarm optimization.Particle expression of feature selection,definition of fitness function and immune mechanisms were given.The selection results were presented through numerical simulation.A comparative experimentation was designed to testify the effectiveness of the method.Three attribute sets:candidate sets,selected sets and deselected sets were used as the input of support vector machine respectively.Results demonstrate that the classification accuracy of selected sets is greatly better than the other.Then the system state can be effectively recognized and the appropriate rule can be adopted for the corresponding manufacturing system state." @default.
- W2393083508 created "2016-06-24" @default.
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- W2393083508 date "2009-01-01" @default.
- W2393083508 modified "2023-09-24" @default.
- W2393083508 title "Scheduling feature selection based on immune binary partial swarm optimization" @default.
- W2393083508 hasPublicationYear "2009" @default.
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