Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks
文献类型：期刊论文
| 作者 | Chang, Fangle2,3 ; Heinemann, Paul H.1
|
| 刊名 | BIOSYSTEMS ENGINEERING
 |
| 出版日期 | 2020-12-01 |
| 卷号 | 200页码:272-283 |
| 关键词 | Hedonic tone Electronic nose zNose (TM) Artificial Neural Networks Multi-sensor data fusion |
| ISSN号 | 1537-5110 |
| DOI | 10.1016/j.biosystemseng.2020.10.005 |
| 通讯作者 | Chang, Fangle(changfl415@gmail.com) |
| 英文摘要 | A Cyranose 320 (eNose) and a Fast Gas Chromatograph (CG) analyser (zNoseTM) were used to measure the headspace odour of solid samples from dairy operations. The measurements of both sensors were trained by Levenberg-Marquardt Back-propagation Neural Network (LMBNN) to match human assessments. A trained human panel was used to assess the odours based on hedonic tone method and provide the model targets. A multi-sensor data fusion approach was developed and applied to integrate the eNose and zNose readings for higher predictive accuracy compared to each sensor alone. Principle Component Analysis, Forward Selection, and Gamma Test were applied to reduce the model input dimensions. Measurement fusion models and information fusion model approaches were applied. The information fusion prediction models were shown to be more accurate than all other models, including single instrument models. The information fusion model based on eNose with Gamma Test data reduction thorn zNose showed the best results of all cases in validation mean square error (0.34 odour units), R value (0.92), probability of the prediction falling within 10% of the target (96%), and probability of the prediction falling within 5% of the target (63%). (C) 2020 IAgrE. Published by Elsevier Ltd. All rights reserved. |
| 资助项目 | USDA National Institute of Food and Agriculture Federal Appropriations[PEN04547] ; USDA National Institute of Food and Agriculture Federal Appropriations[1001036] |
| WOS研究方向 | Agriculture |
| 语种 | 英语 |
| WOS记录号 | WOS:000598489200006 |
| 出版者 | ACADEMIC PRESS INC ELSEVIER SCIENCE |
| 资助机构 | USDA National Institute of Food and Agriculture Federal Appropriations |
| 源URL | [http://ir.ia.ac.cn/handle/173211/42820]  |
| 专题 | 自动化研究所_博士后 |
| 通讯作者 | Chang, Fangle |
| 作者单位 | 1.Penn State Univ, Dept Agr & Biol Engn, 105 Agr Engn Bldg, University Pk, PA 16802 USA 2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 3.Zhejiang Univ, Ningbo Res Inst, Ningbo 315000, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chang, Fangle,Heinemann, Paul H.. Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks[J]. BIOSYSTEMS ENGINEERING,2020,200:272-283. |
| APA | Chang, Fangle,&Heinemann, Paul H..(2020).Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks.BIOSYSTEMS ENGINEERING,200,272-283. |
| MLA | Chang, Fangle,et al."Prediction of human odour assessments based on hedonic tone method using instrument measurements and multi-sensor data fusion integrated neural networks".BIOSYSTEMS ENGINEERING 200(2020):272-283. |
入库方式： OAI收割
来源：自动化研究所
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