Wine Classification Method Based on One-Dimensional Convolutional Neural Network

Leilei Chen ； Jie Yang ； Linlin Chen ； Qiupu Wu ； Xingzhong Xiong

《World Scientific Research Journal》 5卷11期 (2019/11) Pp. 161-167

https://doi.org/10.6911/WSRJ.201911_5(11).0021

摘要

A wine classification model based on one-dimensional convolutional neural network (1DCNN) is proposed for wine classification. The experimental data uses the wine dataset of the UCI machine learning library. Simulation experiments show that the wine classification model based on one-dimensional convolutional neural network has higher classification accuracy than BP neural network and extreme learning machine (ELM) classification model.

關鍵字

One-dimensional convolutional neural network ； BP neural network ； extreme learning machine ； wine classification

參考文獻

R.Boyer, J. Moore. A fast string searching algorithm[J]. Communications of the ACM,1977, 20(10): 762-772.

R. N. Horspool. Practical fast searching in strings[J].Software Practice &Experience, 1980, 10(6): 501-506.

Sainath T N, Mohamed A R, Kingsbury B, et al. Deep convolutional neural networks for LVCSR[C]// IEEE International Conference on Acoustics. 2013.

SP Yuan, JH Wan. Simple Implementation of The Wine Classification with Fuzzy Clustering [J]. Technological horizon,2012(19):96-98+256.

XH Xu, XS Quan, ZF Zhang, XF Hu. A study on the application of PCA and PSO-SVM to the classification of grape wines[J]. Journal of Yunnan University of Nationalities (Natural Sciences Edition),2014,23(06):456-459.