Study of Rough Set-Based Taste Signals Identification
This paper gives a new method of rough set-based on taste signals identification. Further improve the identification accuracy by dividing regions more appropriate. The simulation data and the latest UCI machine learning taste signal data (Wine Quality) are used to verify the new method, and the new method is compared with other identification algorithms. The results fully show the correctness and effectiveness of the proposed identification method based on rough set.
Hao Zhang, Yang Fu and Zhong Tang
Y. J. Sun et al., "Study of Rough Set-Based Taste Signals Identification", Advanced Materials Research, Vols. 354-355, pp. 1170-1173, 2012