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- W4255276542 abstract "Abstract This paper proposed the idea of combining genetic algorithm (GA) with BP (back propagation) neural network, and establishes the TBM tunneling utilization prediction model based on BPNN-GA. Based on the analysis of rock parameters affecting TBM utilization, the rock mass grade, uniaxial compressive strength UCS and joint spacing DPW are selected as the input parameters for TBM utilization prediction. The TBM utilization prediction model based on BPNN-GA is established. The node number and super parameters of hidden layer are determined by empirical formula. The prediction results of bpnn-ga model are combined with the traditional BPNN model The results show that, compared with the traditional BPNN model, BPNN has been improved under the optimization of genetic algorithm, the prediction accuracy on the test set is increased by about 8.95%, and the mean square error is reduced by about 60%. BPNN-GA model does not rely on specific data sets in prediction, showing good portability and generalization." @default.
- W4255276542 created "2022-05-12" @default.
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- W4255276542 date "2021-02-09" @default.
- W4255276542 modified "2023-09-27" @default.
- W4255276542 title "BP Network for Predicting the TBM utilization" @default.
- W4255276542 doi "https://doi.org/10.21203/rs.3.rs-180565/v1" @default.
- W4255276542 hasPublicationYear "2021" @default.
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