A Bio-inspired Ensemble Model for Food Industry Applications

  • Bruno Baruque
  • Emilio Corchado
  • Jordi Rovira
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 73)


This paper presents a soft computing robust solution for the food industry field with the aim of analysing the olfactory properties of Spanish dry-cured ham. A novel topology preserving version of the Visualization Induced SOM (Vi- SOM), based on the application of the Weighted Voting Superposition (WeVoS) summarization algorithm, is presented in order to calculate the best possible visualization of the internal structure of a datasets. The results obtained by this novel model are compared with the ones obtained by its single version -ViSOM- and versus the well-known SOM and WeVOS-SOM. The results clearly demonstrate how the WeVoS-ViSOM outperforms the rest of models.


Soft Computing Electronic Nose Soft Computing Technique Topology Preserve Summarization Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Bruno Baruque
    • 1
  • Emilio Corchado
    • 2
  • Jordi Rovira
    • 1
  1. 1.University of Burgos 
  2. 2.University of Salamanca 

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