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- W2352979921 abstract "Aimed at the limited sample data in the process of mine ventilator fault diagnosis, this paper proposes a fault diagnosis method of mine ventilator based on support vector machine. Support vector machine is a machine learning approach, which has a good learn ability to the limited sample data. Using support vector machine form fault classifiers by learning through the reduced data, then obtained fault diagnosis results of mine ventilator by using the classifier to test the fault samples. The results show that support vector machine has good promotion ability to small samples, it achieving ultimately the purposes of rapid and accurate diagnosis the mine fan faults." @default.
- W2352979921 created "2016-06-24" @default.
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- W2352979921 date "2013-01-01" @default.
- W2352979921 modified "2023-09-26" @default.
- W2352979921 title "The study of fault diagnosis system of mine ventilator based on support vector machine" @default.
- W2352979921 hasPublicationYear "2013" @default.
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