Classification of milk by means of an electronic nose and SVM neural network

被引:140
作者
Brudzewski, K
Osowski, S
Markiewicz, T
机构
[1] Warsaw Univ Technol, Dept Chem, PL-00664 Warsaw, Poland
[2] Warsaw Univ Technol, Inst Theory Elect Engn Measurement & Informat Sys, PL-00661 Warsaw, Poland
关键词
milk classification; support vector machine; neural network;
D O I
10.1016/j.snb.2003.10.028
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
The paper presents the application of support vector machine (SVM) neural approach to the calibration of the electronic nose arrangement for milk recognition. The semiconductor gas sensor array mounted into the measurement test chamber has been used to measure the odour. The pre-processed sensor signals are applied to the SVM neural network performing the role of recognition and classification of the milk. The results of numerical experiments of the recognition of different types of milk have been presented and discussed. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:291 / 298
页数:8
相关论文
共 11 条
  • [1] BURGES C, 2000, KNOWLEDGE DISCOVERY, V1
  • [2] CAPONE S, 2001, SENSOR ACTUAT B-CHEM, V72, P1
  • [3] Influence of heat treatment on the volatile compounds of milk
    Contarini, G
    Povolo, M
    Leardi, R
    Toppino, PM
    [J]. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY, 1997, 45 (08) : 3171 - 3177
  • [4] Crammer Koby., 2000, Proceedings of the Thirteenth Annual Conference on Computa- tional Learning Theory, COLT '00, P35
  • [5] Gas chromatography olfactometry (GC/O) of dairy products
    Friedrich, JE
    Acree, TE
    [J]. INTERNATIONAL DAIRY JOURNAL, 1998, 8 (03) : 235 - 241
  • [6] Haykin S., 1999, Neural Networks: A Comprehensive Foundation, V2nd ed
  • [7] Milk-sense: a volatile sensing system recognises spoilage bacteria and yeasts in milk
    Magan, N
    Pavlou, A
    Chrysanthakis, I
    [J]. SENSORS AND ACTUATORS B-CHEMICAL, 2001, 72 (01) : 28 - 34
  • [8] Lagrangian support vector machines
    Mangasaian, OL
    Musicant, DR
    [J]. JOURNAL OF MACHINE LEARNING RESEARCH, 2001, 1 (03) : 161 - 177
  • [9] Platt JC, 1999, ADVANCES IN KERNEL METHODS, P185
  • [10] SMOLA A, 1998, NV2TR1998030