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- W2386856021 abstract "A new kind of automatic training model was presented for the diagnosis application of complex circs.A judgment criterion used to evaluate the effect of neural network and identify the output pattern was introduced through analyzing the uncertainty elements affecting the training result of neural network.In order to eliminate training uncertainty,an automatic training model was built based on optimizing initial weights of neural network using genetic algorithm.The designed scheme has been applied in downhole problem diagnosis successfully.The downhole problem examples collected in Kekeya area were tested using the diagnosis software fusing both the examples in other area and the virtual examples indicating downhole problem portents.The testing result indicates that the automatic training model for neural network is suitable for computer processing.The experiments show that the model is very promising in neural network modeling." @default.
- W2386856021 created "2016-06-24" @default.
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- W2386856021 date "2011-01-01" @default.
- W2386856021 modified "2023-09-26" @default.
- W2386856021 title "Automatic training of neural network and its diagnosis of complex circs for drilling" @default.
- W2386856021 hasPublicationYear "2011" @default.
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