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Papers: 10.3390/s16040520

https://doi.org/10.3390/s16040520

Enhancing Electronic Nose Performance Based on a Novel QPSO-KELM Model

Cited by: 20
Author(s): Chao Peng, Yan Jia, Shukai Duan, Lidan Wang, Pengfei Jia, Songlin Zhang
Published: over 9 years ago

Software Mentions 3

cran: nose
nose Package for R
Papers that mentioned: 36
Very Likely Science (75)
pypi: nose
nose extends unittest to make testing easier
Papers that mentioned: 36
Very Likely Science (65)
pypi: QDA
A tool for quantitatively measuring the discursive similarity between bodies of text.
Papers that mentioned: 128
Very Likely Science (65)