Abstract
We present how the supervised machine learning techniques can be used to predict quality characteristics in an important chemical engineering application: the wine distillate maturation process. A number of experiments have been conducted with six regression-based algorithms, where the M5' algorithm was proved to be the most appropriate for predicting the organoleptic properties of the matured wine distillates. The rules that are exported by the algorithm are as accurate as human expert's decisions. © Springer-Verlag Berlin Heidelberg 2005.
Cite
CITATION STYLE
Kotsiantis, S. B., Tsekouras, G. E., Raptis, C., & Pintelas, P. E. (2005). Modeling the organoleptic properties of matured wine distillates. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3587 LNAI, pp. 667–673). Springer Verlag. https://doi.org/10.1007/11510888_66
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
