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- W2348730305 abstract "This paper designed a fault diagnosis expert system model of coal mine drilling based on rough sets and integrated neural networks aiming at the actuality of constructing by experience in drilling field. The system constantly trained and learned through associating weight balance adjustment and self-adaptive learning rate algorithm, and verified the existence of accident through forward and reverse mixed reasoning mechanism, and extracted rules adopting value reduction algorithm of rough sets to improve the interpretability of integrated neural networks. The experiment has proved that this system was a kind of special efficiently engineering calculate method in processing such complicated problems as drilling fault, provides powerful guarantee for scientific drilling, improves drilling efficiency and effectively prevents the happening of drilling accidents." @default.
- W2348730305 created "2016-06-24" @default.
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- W2348730305 date "2013-01-01" @default.
- W2348730305 modified "2023-09-28" @default.
- W2348730305 title "Application on Drilling Expert System Based on Rough Sets and Integrated Neural Networks" @default.
- W2348730305 hasPublicationYear "2013" @default.
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