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Sensors 2017, 17(12), 2855; doi:10.3390/s17122855

Stacked Sparse Auto-Encoders (SSAE) Based Electronic Nose for Chinese Liquors Classification

School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
Authors to whom correspondence should be addressed.
Received: 15 October 2017 / Revised: 1 December 2017 / Accepted: 2 December 2017 / Published: 8 December 2017
(This article belongs to the Special Issue Electronic Tongues and Electronic Noses)
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This paper presents a stacked sparse auto-encoder (SSAE) based deep learning method for an electronic nose (e-nose) system to classify different brands of Chinese liquors. It is well known that preprocessing; feature extraction (generation and reduction) are necessary steps in traditional data-processing methods for e-noses. However, these steps are complicated and empirical because there is no uniform rule for choosing appropriate methods from many different options. The main advantage of SSAE is that it can automatically learn features from the original sensor data without the steps of preprocessing and feature extraction; which can greatly simplify data processing procedures for e-noses. To identify different brands of Chinese liquors; an SSAE based multi-layer back propagation neural network (BPNN) is constructed. Seven kinds of strong-flavor Chinese liquors were selected for a self-designed e-nose to test the performance of the proposed method. Experimental results show that the proposed method outperforms the traditional methods. View Full-Text
Keywords: stacked sparse auto-encoders; electronic nose; deep learning; Chinese liquors classification stacked sparse auto-encoders; electronic nose; deep learning; Chinese liquors classification

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Zhao, W.; Meng, Q.-H.; Zeng, M.; Qi, P.-F. Stacked Sparse Auto-Encoders (SSAE) Based Electronic Nose for Chinese Liquors Classification. Sensors 2017, 17, 2855.

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