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- W2356707276 abstract "Pointed to the disadvantages such as low recognizing precision,long training time and limited recognizing range of single neural network in eddy current testing,layered multi-subnet neural network was presented.It was composed by a sumnet and several layered subnets,and could divide a complex task into a series of subtasks,so it could quickly identify whether the defect was existed,and also the defect location and dimension.Because of the improved RBF and wavelet multi-scaling edge detecting were used in each network,the network structure was simplified much.The result showed that layered multi-subnet neural network was suitable to online eddy current testing." @default.
- W2356707276 created "2016-06-24" @default.
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- W2356707276 date "2007-01-01" @default.
- W2356707276 modified "2023-09-23" @default.
- W2356707276 title "Flaw Identification Based on Layered Multi-subnet Neural Networks" @default.
- W2356707276 hasPublicationYear "2007" @default.
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