Abstract
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.
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Baruque, B., Corchado, E., Rovira, J. (2010). A Bio-inspired Ensemble Model for Food Industry Applications. In: Corchado, E., Novais, P., Analide, C., Sedano, J. (eds) Soft Computing Models in Industrial and Environmental Applications, 5th International Workshop (SOCO 2010). Advances in Intelligent and Soft Computing, vol 73. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13161-5_27
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DOI: https://doi.org/10.1007/978-3-642-13161-5_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13160-8
Online ISBN: 978-3-642-13161-5
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