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- W2384170421 abstract "After the field geological investigation of a power station on the Jinsha River,we had obtained basic geological data. According to its geological characteristics,we chose seven influential factors as the input variables of the Artificial Neural Network Model,such as one axis compressive strength of rock( R),rock quality designation( RQD),rock weathering degree,set of joints( Jn), joint roughness coefficient( Jr),fissure anomaly factor( Ja) and groundwater state. The artificial neural network based on the technology of MATLAB was trained,by 116 samples,to be an artificial neural network model which was high stability and reliability.According to the analysis of 36 test data,the artificial neural network model,of which the simulation results was very accurate,was proved to meet fully requirements of the engineering practice." @default.
- W2384170421 created "2016-06-24" @default.
- W2384170421 creator A5063536659 @default.
- W2384170421 date "2015-01-01" @default.
- W2384170421 modified "2023-09-23" @default.
- W2384170421 title "Application of BP Artificial Neural Network in Rock Mass Quality Classification" @default.
- W2384170421 hasPublicationYear "2015" @default.
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